{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "06fb9bb9",
   "metadata": {},
   "source": [
    "# 衡量投资质量的基本指标\n",
    "\n",
    "* 收益率\n",
    "\n",
    "* 风险\n",
    "\n",
    "* 最大回撤\n",
    "\n",
    "本节内容对应《量化投资以python为工具》电子书的265-273页（同时也是书上的247-255页）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c5b64033",
   "metadata": {},
   "outputs": [],
   "source": [
    "from gm.api import *\n",
    "import pandas as pd\n",
    "\n",
    "set_token(\"eea4b28a3ceb7048603d388bb777ebc67de47385\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37f8ef57",
   "metadata": {},
   "source": [
    "## 收益率\n",
    "\n",
    "* 掘金数据的处理\n",
    "\n",
    "* 单期与多期收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b87ebf53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>low</th>\n",
       "      <th>high</th>\n",
       "      <th>eob</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SZSE.000002</td>\n",
       "      <td>24.4712</td>\n",
       "      <td>24.5077</td>\n",
       "      <td>24.2797</td>\n",
       "      <td>24.6263</td>\n",
       "      <td>2020-07-28 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SZSE.000063</td>\n",
       "      <td>38.1755</td>\n",
       "      <td>37.9678</td>\n",
       "      <td>37.6512</td>\n",
       "      <td>38.3832</td>\n",
       "      <td>2020-07-28 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SZSE.002007</td>\n",
       "      <td>57.2363</td>\n",
       "      <td>55.6690</td>\n",
       "      <td>53.7446</td>\n",
       "      <td>57.2363</td>\n",
       "      <td>2020-07-28 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SZSE.000001</td>\n",
       "      <td>13.2359</td>\n",
       "      <td>13.2359</td>\n",
       "      <td>13.0772</td>\n",
       "      <td>13.3252</td>\n",
       "      <td>2020-07-28 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SZSE.000413</td>\n",
       "      <td>2.7600</td>\n",
       "      <td>2.8000</td>\n",
       "      <td>2.7500</td>\n",
       "      <td>2.8400</td>\n",
       "      <td>2020-07-28 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1229</th>\n",
       "      <td>SZSE.000002</td>\n",
       "      <td>19.2828</td>\n",
       "      <td>19.5381</td>\n",
       "      <td>19.0086</td>\n",
       "      <td>19.5760</td>\n",
       "      <td>2021-07-30 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>SZSE.000063</td>\n",
       "      <td>37.0447</td>\n",
       "      <td>38.5862</td>\n",
       "      <td>36.8955</td>\n",
       "      <td>38.9143</td>\n",
       "      <td>2021-07-30 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1231</th>\n",
       "      <td>SZSE.002007</td>\n",
       "      <td>36.5400</td>\n",
       "      <td>36.7900</td>\n",
       "      <td>35.7000</td>\n",
       "      <td>37.2400</td>\n",
       "      <td>2021-07-30 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1232</th>\n",
       "      <td>SZSE.000001</td>\n",
       "      <td>17.9200</td>\n",
       "      <td>17.6900</td>\n",
       "      <td>17.2400</td>\n",
       "      <td>18.0500</td>\n",
       "      <td>2021-07-30 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>SZSE.000413</td>\n",
       "      <td>1.9800</td>\n",
       "      <td>2.0600</td>\n",
       "      <td>1.9700</td>\n",
       "      <td>2.0800</td>\n",
       "      <td>2021-07-30 00:00:00+08:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1234 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           symbol     open    close      low     high  \\\n",
       "0     SZSE.000002  24.4712  24.5077  24.2797  24.6263   \n",
       "1     SZSE.000063  38.1755  37.9678  37.6512  38.3832   \n",
       "2     SZSE.002007  57.2363  55.6690  53.7446  57.2363   \n",
       "3     SZSE.000001  13.2359  13.2359  13.0772  13.3252   \n",
       "4     SZSE.000413   2.7600   2.8000   2.7500   2.8400   \n",
       "...           ...      ...      ...      ...      ...   \n",
       "1229  SZSE.000002  19.2828  19.5381  19.0086  19.5760   \n",
       "1230  SZSE.000063  37.0447  38.5862  36.8955  38.9143   \n",
       "1231  SZSE.002007  36.5400  36.7900  35.7000  37.2400   \n",
       "1232  SZSE.000001  17.9200  17.6900  17.2400  18.0500   \n",
       "1233  SZSE.000413   1.9800   2.0600   1.9700   2.0800   \n",
       "\n",
       "                           eob  \n",
       "0    2020-07-28 00:00:00+08:00  \n",
       "1    2020-07-28 00:00:00+08:00  \n",
       "2    2020-07-28 00:00:00+08:00  \n",
       "3    2020-07-28 00:00:00+08:00  \n",
       "4    2020-07-28 00:00:00+08:00  \n",
       "...                        ...  \n",
       "1229 2021-07-30 00:00:00+08:00  \n",
       "1230 2021-07-30 00:00:00+08:00  \n",
       "1231 2021-07-30 00:00:00+08:00  \n",
       "1232 2021-07-30 00:00:00+08:00  \n",
       "1233 2021-07-30 00:00:00+08:00  \n",
       "\n",
       "[1234 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#000413 东旭光电，000063 中兴通讯，002007 华兰生物，000001 平安银行，000002 万科A\n",
    "stock_n = history(symbol='SZSE.000413,SZSE.000063,SZSE.002007,SZSE.000001,SZSE.000002', frequency='1d', start_time='2020-07-28',  end_time='2021-07-30', fields='symbol,open, close, low, high, eob', adjust=ADJUST_PREV, df= True)\n",
    "stock_n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e4ec0853",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2020-07-28'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(stock_n.eob[0].date())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f208c5e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_str(x):\n",
    "    return str(x.date())\n",
    "\n",
    "stock_n.eob=stock_n.eob.apply(time_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cfcf522d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>symbol</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>low</th>\n",
       "      <th>high</th>\n",
       "      <th>eob</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SZSE.000002</td>\n",
       "      <td>24.4712</td>\n",
       "      <td>24.5077</td>\n",
       "      <td>24.2797</td>\n",
       "      <td>24.6263</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SZSE.000063</td>\n",
       "      <td>38.1755</td>\n",
       "      <td>37.9678</td>\n",
       "      <td>37.6512</td>\n",
       "      <td>38.3832</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SZSE.002007</td>\n",
       "      <td>57.2363</td>\n",
       "      <td>55.6690</td>\n",
       "      <td>53.7446</td>\n",
       "      <td>57.2363</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SZSE.000001</td>\n",
       "      <td>13.2359</td>\n",
       "      <td>13.2359</td>\n",
       "      <td>13.0772</td>\n",
       "      <td>13.3252</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SZSE.000413</td>\n",
       "      <td>2.7600</td>\n",
       "      <td>2.8000</td>\n",
       "      <td>2.7500</td>\n",
       "      <td>2.8400</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1224</th>\n",
       "      <td>SZSE.000002</td>\n",
       "      <td>19.5760</td>\n",
       "      <td>19.4814</td>\n",
       "      <td>19.1126</td>\n",
       "      <td>19.7178</td>\n",
       "      <td>2021-07-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1225</th>\n",
       "      <td>SZSE.000063</td>\n",
       "      <td>37.9099</td>\n",
       "      <td>37.3431</td>\n",
       "      <td>36.8458</td>\n",
       "      <td>38.0690</td>\n",
       "      <td>2021-07-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1226</th>\n",
       "      <td>SZSE.002007</td>\n",
       "      <td>37.1500</td>\n",
       "      <td>36.7900</td>\n",
       "      <td>36.4100</td>\n",
       "      <td>37.4400</td>\n",
       "      <td>2021-07-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1227</th>\n",
       "      <td>SZSE.000001</td>\n",
       "      <td>17.9100</td>\n",
       "      <td>17.9600</td>\n",
       "      <td>17.7800</td>\n",
       "      <td>18.2400</td>\n",
       "      <td>2021-07-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1228</th>\n",
       "      <td>SZSE.000413</td>\n",
       "      <td>1.9700</td>\n",
       "      <td>1.9900</td>\n",
       "      <td>1.9700</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>2021-07-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1229 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           symbol     open    close      low     high         eob\n",
       "0     SZSE.000002  24.4712  24.5077  24.2797  24.6263  2020-07-28\n",
       "1     SZSE.000063  38.1755  37.9678  37.6512  38.3832  2020-07-28\n",
       "2     SZSE.002007  57.2363  55.6690  53.7446  57.2363  2020-07-28\n",
       "3     SZSE.000001  13.2359  13.2359  13.0772  13.3252  2020-07-28\n",
       "4     SZSE.000413   2.7600   2.8000   2.7500   2.8400  2020-07-28\n",
       "...           ...      ...      ...      ...      ...         ...\n",
       "1224  SZSE.000002  19.5760  19.4814  19.1126  19.7178  2021-07-29\n",
       "1225  SZSE.000063  37.9099  37.3431  36.8458  38.0690  2021-07-29\n",
       "1226  SZSE.002007  37.1500  36.7900  36.4100  37.4400  2021-07-29\n",
       "1227  SZSE.000001  17.9100  17.9600  17.7800  18.2400  2021-07-29\n",
       "1228  SZSE.000413   1.9700   1.9900   1.9700   2.0000  2021-07-29\n",
       "\n",
       "[1229 rows x 6 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_n[stock_n.eob<\"2021-07-30\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0ea82ea4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>symbol</th>\n",
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       "      <th>1</th>\n",
       "      <td>SZSE.000063</td>\n",
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       "      <td>2020-07-28</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SZSE.002007</td>\n",
       "      <td>55.6690</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SZSE.000001</td>\n",
       "      <td>13.2359</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SZSE.000413</td>\n",
       "      <td>2.8000</td>\n",
       "      <td>2020-07-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1229</th>\n",
       "      <td>SZSE.000002</td>\n",
       "      <td>19.5381</td>\n",
       "      <td>2021-07-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1230</th>\n",
       "      <td>SZSE.000063</td>\n",
       "      <td>38.5862</td>\n",
       "      <td>2021-07-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1231</th>\n",
       "      <td>SZSE.002007</td>\n",
       "      <td>36.7900</td>\n",
       "      <td>2021-07-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1232</th>\n",
       "      <td>SZSE.000001</td>\n",
       "      <td>17.6900</td>\n",
       "      <td>2021-07-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1233</th>\n",
       "      <td>SZSE.000413</td>\n",
       "      <td>2.0600</td>\n",
       "      <td>2021-07-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1234 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           symbol    close         eob\n",
       "0     SZSE.000002  24.5077  2020-07-28\n",
       "1     SZSE.000063  37.9678  2020-07-28\n",
       "2     SZSE.002007  55.6690  2020-07-28\n",
       "3     SZSE.000001  13.2359  2020-07-28\n",
       "4     SZSE.000413   2.8000  2020-07-28\n",
       "...           ...      ...         ...\n",
       "1229  SZSE.000002  19.5381  2021-07-30\n",
       "1230  SZSE.000063  38.5862  2021-07-30\n",
       "1231  SZSE.002007  36.7900  2021-07-30\n",
       "1232  SZSE.000001  17.6900  2021-07-30\n",
       "1233  SZSE.000413   2.0600  2021-07-30\n",
       "\n",
       "[1234 rows x 3 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_n[[\"symbol\",\"close\",\"eob\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "031060b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>symbol</th>\n",
       "      <th>SZSE.000001</th>\n",
       "      <th>SZSE.000002</th>\n",
       "      <th>SZSE.000063</th>\n",
       "      <th>SZSE.000413</th>\n",
       "      <th>SZSE.002007</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eob</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-28</th>\n",
       "      <td>13.2359</td>\n",
       "      <td>24.5077</td>\n",
       "      <td>37.9678</td>\n",
       "      <td>2.80</td>\n",
       "      <td>55.6690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-29</th>\n",
       "      <td>13.4344</td>\n",
       "      <td>24.7266</td>\n",
       "      <td>39.1153</td>\n",
       "      <td>2.84</td>\n",
       "      <td>59.3492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>13.2657</td>\n",
       "      <td>24.5168</td>\n",
       "      <td>38.4921</td>\n",
       "      <td>2.79</td>\n",
       "      <td>60.4899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>13.2359</td>\n",
       "      <td>24.4803</td>\n",
       "      <td>38.7493</td>\n",
       "      <td>2.80</td>\n",
       "      <td>64.4082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>13.4840</td>\n",
       "      <td>24.8816</td>\n",
       "      <td>39.0757</td>\n",
       "      <td>2.86</td>\n",
       "      <td>70.8460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-26</th>\n",
       "      <td>18.8000</td>\n",
       "      <td>20.2001</td>\n",
       "      <td>35.9508</td>\n",
       "      <td>2.08</td>\n",
       "      <td>36.4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-27</th>\n",
       "      <td>17.7600</td>\n",
       "      <td>19.0653</td>\n",
       "      <td>36.5674</td>\n",
       "      <td>2.08</td>\n",
       "      <td>35.8900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>17.7500</td>\n",
       "      <td>19.3774</td>\n",
       "      <td>37.0845</td>\n",
       "      <td>1.96</td>\n",
       "      <td>36.9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>17.9600</td>\n",
       "      <td>19.4814</td>\n",
       "      <td>37.3431</td>\n",
       "      <td>1.99</td>\n",
       "      <td>36.7900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>17.6900</td>\n",
       "      <td>19.5381</td>\n",
       "      <td>38.5862</td>\n",
       "      <td>2.06</td>\n",
       "      <td>36.7900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>247 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "symbol      SZSE.000001  SZSE.000002  SZSE.000063  SZSE.000413  SZSE.002007\n",
       "eob                                                                        \n",
       "2020-07-28      13.2359      24.5077      37.9678         2.80      55.6690\n",
       "2020-07-29      13.4344      24.7266      39.1153         2.84      59.3492\n",
       "2020-07-30      13.2657      24.5168      38.4921         2.79      60.4899\n",
       "2020-07-31      13.2359      24.4803      38.7493         2.80      64.4082\n",
       "2020-08-03      13.4840      24.8816      39.0757         2.86      70.8460\n",
       "...                 ...          ...          ...          ...          ...\n",
       "2021-07-26      18.8000      20.2001      35.9508         2.08      36.4600\n",
       "2021-07-27      17.7600      19.0653      36.5674         2.08      35.8900\n",
       "2021-07-28      17.7500      19.3774      37.0845         1.96      36.9000\n",
       "2021-07-29      17.9600      19.4814      37.3431         1.99      36.7900\n",
       "2021-07-30      17.6900      19.5381      38.5862         2.06      36.7900\n",
       "\n",
       "[247 rows x 5 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(stock_n,index=[\"eob\"],columns=[\"symbol\"],values=[\"close\"]).close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "67176aab",
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_close=pd.pivot_table(stock_n,index=[\"eob\"],columns=[\"symbol\"],values=[\"close\"]).close"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3e48bf87",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>symbol</th>\n",
       "      <th>SZSE.000001</th>\n",
       "      <th>SZSE.000002</th>\n",
       "      <th>SZSE.000063</th>\n",
       "      <th>SZSE.000413</th>\n",
       "      <th>SZSE.002007</th>\n",
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       "      <th>eob</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-28</th>\n",
       "      <td>13.2359</td>\n",
       "      <td>24.5077</td>\n",
       "      <td>37.9678</td>\n",
       "      <td>2.80</td>\n",
       "      <td>55.6690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-29</th>\n",
       "      <td>13.4344</td>\n",
       "      <td>24.7266</td>\n",
       "      <td>39.1153</td>\n",
       "      <td>2.84</td>\n",
       "      <td>59.3492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>13.2657</td>\n",
       "      <td>24.5168</td>\n",
       "      <td>38.4921</td>\n",
       "      <td>2.79</td>\n",
       "      <td>60.4899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>13.2359</td>\n",
       "      <td>24.4803</td>\n",
       "      <td>38.7493</td>\n",
       "      <td>2.80</td>\n",
       "      <td>64.4082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>13.4840</td>\n",
       "      <td>24.8816</td>\n",
       "      <td>39.0757</td>\n",
       "      <td>2.86</td>\n",
       "      <td>70.8460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-26</th>\n",
       "      <td>18.8000</td>\n",
       "      <td>20.2001</td>\n",
       "      <td>35.9508</td>\n",
       "      <td>2.08</td>\n",
       "      <td>36.4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-27</th>\n",
       "      <td>17.7600</td>\n",
       "      <td>19.0653</td>\n",
       "      <td>36.5674</td>\n",
       "      <td>2.08</td>\n",
       "      <td>35.8900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>17.7500</td>\n",
       "      <td>19.3774</td>\n",
       "      <td>37.0845</td>\n",
       "      <td>1.96</td>\n",
       "      <td>36.9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>17.9600</td>\n",
       "      <td>19.4814</td>\n",
       "      <td>37.3431</td>\n",
       "      <td>1.99</td>\n",
       "      <td>36.7900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>17.6900</td>\n",
       "      <td>19.5381</td>\n",
       "      <td>38.5862</td>\n",
       "      <td>2.06</td>\n",
       "      <td>36.7900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>247 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "symbol      SZSE.000001  SZSE.000002  SZSE.000063  SZSE.000413  SZSE.002007\n",
       "eob                                                                        \n",
       "2020-07-28      13.2359      24.5077      37.9678         2.80      55.6690\n",
       "2020-07-29      13.4344      24.7266      39.1153         2.84      59.3492\n",
       "2020-07-30      13.2657      24.5168      38.4921         2.79      60.4899\n",
       "2020-07-31      13.2359      24.4803      38.7493         2.80      64.4082\n",
       "2020-08-03      13.4840      24.8816      39.0757         2.86      70.8460\n",
       "...                 ...          ...          ...          ...          ...\n",
       "2021-07-26      18.8000      20.2001      35.9508         2.08      36.4600\n",
       "2021-07-27      17.7600      19.0653      36.5674         2.08      35.8900\n",
       "2021-07-28      17.7500      19.3774      37.0845         1.96      36.9000\n",
       "2021-07-29      17.9600      19.4814      37.3431         1.99      36.7900\n",
       "2021-07-30      17.6900      19.5381      38.5862         2.06      36.7900\n",
       "\n",
       "[247 rows x 5 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_close"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3322ab2c",
   "metadata": {},
   "source": [
    "## classwork1\n",
    "\n",
    "* 请计算'sz000413'的第一期收益率（2020-07-28收盘价买入，通过2020-07-29收盘价看收益）\n",
    "\n",
    "* 请计算stockset中所有股票所有期的单期收益率，并作图(shift函数的使用)\n",
    "\n",
    "* 请计算'sz000413'的2020-07-28收盘价买入，通过2020-07-30卖出的收益率\n",
    "\n",
    "* 请计算所有股票所有天的二期收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "24e40358",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.003571425226269879"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(stock_close[\"SZSE.000413\"][\"2020-07-30\"]-stock_close[\"SZSE.000413\"][\"2020-07-28\"])/stock_close[\"SZSE.000413\"][\"2020-07-28\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "47fefa83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>symbol</th>\n",
       "      <th>SZSE.000001</th>\n",
       "      <th>SZSE.000002</th>\n",
       "      <th>SZSE.000063</th>\n",
       "      <th>SZSE.000413</th>\n",
       "      <th>SZSE.002007</th>\n",
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       "    <tr>\n",
       "      <th>eob</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-29</th>\n",
       "      <td>13.2359</td>\n",
       "      <td>24.5077</td>\n",
       "      <td>37.9678</td>\n",
       "      <td>2.80</td>\n",
       "      <td>55.6690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>13.4344</td>\n",
       "      <td>24.7266</td>\n",
       "      <td>39.1153</td>\n",
       "      <td>2.84</td>\n",
       "      <td>59.3492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>13.2657</td>\n",
       "      <td>24.5168</td>\n",
       "      <td>38.4921</td>\n",
       "      <td>2.79</td>\n",
       "      <td>60.4899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>13.2359</td>\n",
       "      <td>24.4803</td>\n",
       "      <td>38.7493</td>\n",
       "      <td>2.80</td>\n",
       "      <td>64.4082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-26</th>\n",
       "      <td>20.1000</td>\n",
       "      <td>21.8551</td>\n",
       "      <td>36.1696</td>\n",
       "      <td>2.10</td>\n",
       "      <td>38.1200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-27</th>\n",
       "      <td>18.8000</td>\n",
       "      <td>20.2001</td>\n",
       "      <td>35.9508</td>\n",
       "      <td>2.08</td>\n",
       "      <td>36.4600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>17.7600</td>\n",
       "      <td>19.0653</td>\n",
       "      <td>36.5674</td>\n",
       "      <td>2.08</td>\n",
       "      <td>35.8900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>17.7500</td>\n",
       "      <td>19.3774</td>\n",
       "      <td>37.0845</td>\n",
       "      <td>1.96</td>\n",
       "      <td>36.9000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>17.9600</td>\n",
       "      <td>19.4814</td>\n",
       "      <td>37.3431</td>\n",
       "      <td>1.99</td>\n",
       "      <td>36.7900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>247 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "symbol      SZSE.000001  SZSE.000002  SZSE.000063  SZSE.000413  SZSE.002007\n",
       "eob                                                                        \n",
       "2020-07-28          NaN          NaN          NaN          NaN          NaN\n",
       "2020-07-29      13.2359      24.5077      37.9678         2.80      55.6690\n",
       "2020-07-30      13.4344      24.7266      39.1153         2.84      59.3492\n",
       "2020-07-31      13.2657      24.5168      38.4921         2.79      60.4899\n",
       "2020-08-03      13.2359      24.4803      38.7493         2.80      64.4082\n",
       "...                 ...          ...          ...          ...          ...\n",
       "2021-07-26      20.1000      21.8551      36.1696         2.10      38.1200\n",
       "2021-07-27      18.8000      20.2001      35.9508         2.08      36.4600\n",
       "2021-07-28      17.7600      19.0653      36.5674         2.08      35.8900\n",
       "2021-07-29      17.7500      19.3774      37.0845         1.96      36.9000\n",
       "2021-07-30      17.9600      19.4814      37.3431         1.99      36.7900\n",
       "\n",
       "[247 rows x 5 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_close.shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "eff3d155",
   "metadata": {},
   "outputs": [],
   "source": [
    "r1=((stock_close-stock_close.shift(1))/stock_close.shift(1)).loc[\"2020-07-29\":]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "27970096",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>0.0022</td>\n",
       "      <td>0.0004</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>-0.0036</td>\n",
       "      <td>0.0866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>-0.0148</td>\n",
       "      <td>-0.0100</td>\n",
       "      <td>-0.0094</td>\n",
       "      <td>-0.0141</td>\n",
       "      <td>0.0852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>0.0165</td>\n",
       "      <td>0.0149</td>\n",
       "      <td>0.0152</td>\n",
       "      <td>0.0251</td>\n",
       "      <td>0.1712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-04</th>\n",
       "      <td>0.0525</td>\n",
       "      <td>0.0335</td>\n",
       "      <td>-0.0074</td>\n",
       "      <td>0.0321</td>\n",
       "      <td>0.0547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-05</th>\n",
       "      <td>0.0125</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>-0.0091</td>\n",
       "      <td>0.0315</td>\n",
       "      <td>-0.0175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-26</th>\n",
       "      <td>-0.0775</td>\n",
       "      <td>-0.0797</td>\n",
       "      <td>-0.0267</td>\n",
       "      <td>-0.0326</td>\n",
       "      <td>-0.0627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-27</th>\n",
       "      <td>-0.1164</td>\n",
       "      <td>-0.1277</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>-0.0095</td>\n",
       "      <td>-0.0585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>-0.0559</td>\n",
       "      <td>-0.0407</td>\n",
       "      <td>0.0315</td>\n",
       "      <td>-0.0577</td>\n",
       "      <td>0.0121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>0.0113</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>0.0212</td>\n",
       "      <td>-0.0433</td>\n",
       "      <td>0.0251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>-0.0034</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>0.0405</td>\n",
       "      <td>0.0510</td>\n",
       "      <td>-0.0030</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "symbol      SZSE.000001  SZSE.000002  SZSE.000063  SZSE.000413  SZSE.002007\n",
       "eob                                                                        \n",
       "2020-07-30       0.0022       0.0004       0.0138      -0.0036       0.0866\n",
       "2020-07-31      -0.0148      -0.0100      -0.0094      -0.0141       0.0852\n",
       "2020-08-03       0.0165       0.0149       0.0152       0.0251       0.1712\n",
       "2020-08-04       0.0525       0.0335      -0.0074       0.0321       0.0547\n",
       "2020-08-05       0.0125       0.0026      -0.0091       0.0315      -0.0175\n",
       "...                 ...          ...          ...          ...          ...\n",
       "2021-07-26      -0.0775      -0.0797      -0.0267      -0.0326      -0.0627\n",
       "2021-07-27      -0.1164      -0.1277       0.0110      -0.0095      -0.0585\n",
       "2021-07-28      -0.0559      -0.0407       0.0315      -0.0577       0.0121\n",
       "2021-07-29       0.0113       0.0218       0.0212      -0.0433       0.0251\n",
       "2021-07-30      -0.0034       0.0083       0.0405       0.0510      -0.0030\n",
       "\n",
       "[245 rows x 5 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2=((stock_close-stock_close.shift(2))/stock_close.shift(2)).loc[\"2020-07-30\":]\n",
    "r2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5ddd5263",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='eob'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JwLqZSuB6tp/Edm10dJR3vvOdDA4O4vs+BxxwAO9+97s5+eSTWb16dRtltGLFCt7xjndwwQUXsH79eiqVCosWLeIrX8k6HrTFJMC2Mb3nnnv4yle+wte//nXmz5/PP/3TP3H88ccD8M///M/Mnz8fgE996lOce+65XHTRRRxzzDH87d/+LQDPO/15/PxnP+dZRz2LOd1z+OY3vwmA7/t88Ytf5IwzzkApxRve8AYOO8wisgsvvJBXvOIVXHLJJey9995cfvnl2Zj23XdfhoeHiaKIK6+8kuuuu26H5NCLNi1OQghxJvAFwAO+boy5eMz7wr3/AqABvN4Yc5cQ4mDgssKm+wP/bIz5dyHER4A3AVvcex90vSdm1IpIYip00/33R5TK8+jejZ1EczSiXAuQcvq5zZmtuHbHnCEqb1tB94F6xJxqgNfhmqULgihM3P475yS0NpNfmMz2k9iuHXvssR1TVbf1XP/617/u+Hoayxhrxx13HF//+tezv9/whjfwhje8Ydx2+++/P7fddtv4Awi46NMX0VPqYe857VTlC17wAl7wgheM22XBggXccMMNHcdTbLM6XbbTdJMQwgO+BDwfOBR4lRBirOt6PnCg+/dm4MsAxpiHjDFHG2OOBo7FOpArCvt9Pn3/yXAQ0I4kJks3teoxd9wNmxcds9siiThSfOdDv2fl7Ztm5Pha/+XFJKJEc/K/3ciP71rbeUc3ntgF1vVOBtanhiRm+0n8JdlfuizHCcAjxpjHjDER8ANgLEl2NvBtY+0WYK4QYumYbU4DHjXGPDENY9phKyKJya7q0gfbCLnbxiTiliIOFfWhcEaOP5OyHHkx3ZPb4zpMFCOthM3DrY77pYHrKJ4euklPJbtptp/EX4Rl2k1/4bIcewJrCn+vda9NdZtzge+Pee0dQoh7hBDfEELM63RyIcSbhRB3CCHu2LJlS6dNpmTtSGKyTsLlywtvt62TUImbCCe7Up2iaZ6EOoknucd1erpoomvmJvSUbppKDKuTWSQx2TqJ2X4SfwnWKQV2d7PpcBKdCO6xn3ib2wghSsBZwOWF978MPAU4GtgAdGwjZYz5qjHmOGPMcYsWLZrCsDtbWwrsJJ9XlaRIwtttVwRp/cdMOYlMu2kmKq7jXdOZLkkptIkmbrcgiB2S2NmQidYGM4PZTSrRu+39+dduf+lOYi2wV+Hv5cBYAZrtbfN84C5jTEaYG2M2GWOUsSktX8PSWjNubXTTlJGE3H2RRDrG3U3aYhKWS548uUhCue9/otTWNNsqjtLA9dTHp7Xh6799jGakbM9sM8nvaIqB66iZcMk//pbV9/dPeYyzNnOWOYfd10dMi5O4HThQCLGfQwTnAleP2eZq4HXC2knAkDFmQ+H9VzGGahoTs3gJcN80jHW7Vqy4ZtIKCXlMYnddqWmHdiZNZ0z1+H/GxXQTxSTS08UTre5VGrhOnczUv/sHNgzzsZ8/yG9Xbsmcw6Roq3Rwk8wmazVi4lAx0tec8hhnbQYt8xG757wB0+AkjDEJ8A7gWuBB4IfGmPuFEG8VQrzVbfYL4DHgESwq+Lt0fyFEDVgB/GTMoT8thLhXCHEPcCrw7p0d62RsRyqucyex+8ck1EzRTTMoy/FkqcBOFUmkE/XOBK7TtNlEmyk6ialRcBMde93ouqnXh/wZ2Z+LVPhzn/bcnZYKv/766zn22GM54ogjOPbYYydM552qTUudhEtP/cWY175S+N0Ab59g3wawoMPr503H2KZqRYG/yQYiUypHy903u2mmYxI7rH80CXuyVGDHTpapQ00muGbpIsJSlN4OBa5TR6QKNRKTiktMkW5Kv/fi97+1uZUX/uSFfOHUL/CcvZ4z0a5/tlaUCi+Xy2zdupUoirj77ruzbe69915e8IIXtEmF33XXXfT29jI6OkoxGebf/u3fMiXXTpZKhd9xxx0IITj22GM566yzmDdvXiYVfu655/LWt76VSy65hLe97W3ceN2NrH5sNdffcT39D/fztre9jVtvvTWTCr/++utZvnw5xx9/PGeddRaHHnpoJhV+4YUXcvHFF3PxxRfzqU99ioULF/LTn/6UZcuWcd9993HGGWdkQoI7Y7OyHGMsKdJNk44hFgLXu6uTUDPrJDKp8BlpOvTkZDeNHft2kcQ0BK5Tx6C0yRIlJvUdTVHgLz1P8djD0TDKKPpbf5lxij8HqfBrf3GtlQoXOy8Vfswxx2Sf77DDDqPVahGGO5/yPivLgZ1AWyMx5Zq/QxXXfw51EupJiknMbI/rJze7KaWC4gkQQkp/pffMDgWu3aETbfJxzEDguhPdFCtHk81ARlqb/fJC2Hjv9B5zyRHw/Iu3uclkpMKf8YxncPoLTgd2jVT4xvUbWbJsSfbdT5dU+I9//GOOOeaYzEHujM0iCWDL6hG+deHvWPvQwA6lwOqkkN1kzG4ZvJ7xFNiZRBJPUsX1uJhE6iSSiZBE6iQcktiB711lSEJ3pIQmtCmmwHY6dvpdzUg3wd3AJiMVfuHHLuTx4ceBXSsVPpV9tmf3338/73//+/nv//7vSW2/PZtFEoDnW1+pE0MSaaQv0MnkJ/u2wDXYyczzZmSsO2p6hummJ6Pi+snObsqDytsOXOdIYurXNk2zbgtcTwbtZXTT5K5JFu8oIgmdBtxnGElsZ8U/k7Y9qfBKtUK9Wc+2f7KlwpcsW2Klwh23vbNS4WvXruUlL3kJ3/72t3nKU56yo5etzWaRBLmTUIlGJYqgbCf4yS4MxzmJ3TDDKa+4nlklVaUVN6+/mc2N6euWlQr8zRRCm0i7KZ3AJ6q4NpmTmLrA30A9YuNQKzuH0ib7fUbopg5I4klzErvIJiMVXpTF2BVS4StesIKrL7sarfVOS4UPDg7ywhe+kE9+8pM885nP3Ikr126zToIxTiI2+IFzElPMbjLCHmdX0U1Gm2wsYy2PScwskkh0wjtveCeXPXTZdvaYvM20LEcqTjiWdtku3ZTul6ROYvLn/NjPH+Tt/3NXgW6aOHAdrV7NoJtg8nOPp5t+fs8G3n3Z3R3Pl8U7CoPMnMRMxyR2kY2OjnL++edz6KGHcuSRR/LAAw/wyle+kp/97Gd897vf5eijj+Z5T38eLz3lpbz3ve8ljmMuuOACnvrUp3L00Udz2WWX8YUvfCE73nvf+9621Nkoirjjjjt44xvfCNAmFX788cePkwr/3Oc+xwEHHEBfX18mFX7KilNYvs9yzjz+TN70pjfxX//1X0C7VPghhxzCK17xijap8Ouvv54DDzyQ66+/ngsvvBCAL37xizzyyCP867/+azbG6WhtOks3MRZJaPxgapN9W+AadhmSuP+367jz2ic4/xPjVxEzrd2UrsZbqkWkIyIVTduxd5UKbFKgm7auHWXz48Mc+qw8O8YU6SYxtcB1fz1kqBnndJPS2aIk/fm9D9/CMSv2ZuEdP6HvK//NnLPOQpZKFuKa8dlNt67q49r7N3Y8XxaTKCx8UgTxl4okJiMVvn50PQOtAZ46/6l40nvSpcKFEFz06YsAOGxhewe/qUqFX3TRRVx00UUdx7kzNoskAC+wAaHMSZSmSjcVBP6YOemL7dnQ1haj/WFHNDHTdFM6wdZjy+9OZ5bTTGc3TZSZVaSbHvjtOm663FIXf7xhDaMDYR6TSJHEFL72WBnXP8L+XazF0MrGwwY3NRja0kSP2muq6447LzqzwgQfKz1hTUenGowUScxIN8FtWDNW/Gnj8MSaWE+iZXTTLqp4Lp53d0x4gVkkARSQRGxQsabSHQCTn+zHxSR2UQVrmsGURBqv2u7/0wysnVUqnfDcbqIZjUbteabzGsxwncR2A9dKEzYTtDI0R6PMWVQyuklBMLVrGymNMibLiNJjnER2TxmTOQc9Ogrz5rVnNBWuSZQY4gmuUXo8tSsC12MsjBVRoomVxvd28Tp1F8titDkJDKKjFuqutVkkQQe6qTQ1uinj+3cx3ZSihWLVeP7ekxOTGI2tk5jOtMoZj0l0QBLGGOpbrM5RrDRRM0Gr9jTVFNlolab/Tn58UaLRJq+yTgpxD61N9l0a45wD+c+2AroxSMKYzgF00wlJqLQI8Mm9X1OEtjssnHd5PwcDJVXZtWPYjs06CUB6Y+imYEfppl0buM6RRCcn8eTEJGaSboKZubadYhIbHxvmT998mIVKkChD2EzsBJzWm9gOQXb/eOqB61hp22TIfZzixG4KNRPjkAS0ZzQVrnNaGd6pQrxTxXWKIGYkbXkbprPV+6zJxKe3tYhAtRe9GWN4fOhxRqKRXTSy3GadBDZ45PnSOQmTI4kdpZt2OZLYVkxiZpFE6iSmk24qOomZQBOdFGxbozbw3qUFkdJETYcWCkWJKZJQauoV11GiUTqnm4pxJKUKSELnTkJlTqKIJMY7iU5Cg50C17sqJpEjiV3rJkyh8HVXIgkAgWijnrTR1OM6zbDVrky9C2zWSTjzfDF9SGIXSXOkE1i8TbppZimb9EafXiRRWOnOgAPuhCTSSTUwNqgcNR1ayJCEyRyWzqTCJ3/O2MUk0smpDUm0xSRAN1Ikse3AdVrP0SkgbDogiV0VkzC7CZKI16yhu7/pxrKrR9NeZZ2NZyRgdKBz+9wny2adhDMvkKjEBq6niiTUWCSxi5yE3gaS0DNNN+mxmUEzELhmZlZ8nQLX6XUqIWxMouXSRZ0D1spkDiuNSUwpcJ1oG3tI6yQmiEmgDSqlm+odkERhzGk9R6f+FzndlG+fyXLsMiQx8+fallT48WecwcnPP5sT9zuRD134IeDJlwo3Gj74kffxvJNO5WnHPK2tmO+mG27iGc8+nmNOPKJNKhzgP//zPzn44IM57LDDeN/73gfAbbfdlo3vqKOO4oorrpiWazib3eTM8yWx61U89RTYMXUSu8hJbDtwnVIjM0s3ZeeboZjETNJNxTGnk2nJ2Mk3RRKpAy5OttsKXL/pujdx4tITeeMRb2x7PVKWasqcxNjsphT5mRxBdIxJdKCbOgWus3t0G9lNxhhiZSj5M7t2fLKQxPakwsOVK7nroQd4yVvewt+96+92iVT4/95wI6tWPcqvbr6RDY+tzaTCkyThYxd+jB9/92fss9fenP6iUzKp8BtvvJGrrrqKe+65h3K5nBXMHX744dxxxx34vs+GDRs46qijeNGLXpQJC+6oTcvdIIQ4UwjxkBDiESHEhR3eF0KI/3Dv3yOEeFrhvcddc6G7hRB3FF6fL4S4Xgix0v2cNx1jncikLzPeOSumm3JMYvegm7Ydk5jZgrTU9DRegyfLSbQhCZ3STQISk01sqU6TKaz8VZIiifHHfmTwEVYNrRr3eqxsTCI97jgnobcRk5gguynaRuB6W3RT+vPXf9rMsf96PfVwZumnJysmsT2p8GarxZsueB8Xfeoilixdskukwq+/5jpefs6rkEJy4okntkmF773v3uyz974EQbtU+Je//GUuvPDC7HOl2k21Wi1zCK1Wa9KCgNuznUYSQggP+BK2u9xa4HYhxNXGmAcKmz0fOND9OxH4svuZ2qnGmK1jDn0hcIMx5mLneC4E3r+z453IPF8St1IkMcWK60wFdtfSTbsqBdYYM47TnU6phycru6kdSTi6yYBXpGg6IIl0Nd8JSWijO1JvUaLxpMjrJIp8tDbZ96WGh3NaK41JtNFN+e9R+v1PNnA9JgV27UCTkTBhuBXTVZ4+kuFTt32KP/X/Kfs7TDSJ0pQDD1/u2ET21PlP5f0nbHs62J5U+Ac//WlOPOYYTj3zVIwxT65U+Jo1qNFRNm3YyJ7L9gRsHKIoFb5kzyW4N9qkwh9++GF++9vf8qEPfYhKpcJnPvMZjj/+eABuvfVW3vCGN/DEE0/wne98Z6dRBEwPkjgBeMQY85gxJgJ+AJw9ZpuzgW8ba7cAc8f0sO5kZwMpqXcp8OJpGOuE5vmCqOWQxI7STdLtt6uym7aRAjuTMYlO1NK0xiSKSGIGru22YhIB4BVOmSm+Fq6jl9FV44+d6KTj9UmRREoNpfSSPbfO0EnzwXxynUydBHQOXHdMgTXtshx58eDMrvDNk8Q3bU8q/Mbf/56Pv/+9bijmSZUKRymSTZvyOcbk2U1CiPxeNLS9DrbCf2BggFtuuYV/+7d/4xWveEV2jhNPPJH777+f22+/nU9+8pO0Wjsf9J6O5cKewJrC32tpRwkTbbMnsAF7q1wnhDDAfxtjvuq2WWyM2QBgjNkghNiDDiaEeDPwZoC99957hz+E50tao3ZlNVW6KXITh5ZpxfUuqpNIA5dPcgpsJ4cwY3USM4DSto0kBGWTr3YzJJHk28ptqLd2QhJaGxJtkLKQ3VSkm7RBtdwqfzSXse4YuC5cjzRg3Slw3ZFuUu0psCmambAT3w7a2BX/qq11Rloxe86tsqB755vibMu2JRX+w89/nq5qlT7y72HapcKffhwLe7vGSYUv3WMP0JolS5eybv06DuMQjDGZJPhIY4SN6zbaCmzTLhW+fPlyzjnnnGysUkq2bt3KokWLsnMfcsghdHV1cd9993Hcccft1DWcDiTRCS+OvUu3tc0zjTFPw1JSbxdCnDyVkxtjvmqMOc4Yc1zxIk3VPF9mGSw5kpjchFpv2RaBu1rgL6Uotl1MN3OTbNFmrE7iScpuSusWAmMpp9Ryuil/UZqJaR5l1LhrkcYOitlNxRiOVgbVstkvRSfRsU6iQzFdR9prG3USKZIo9raYSctiEjN6FisV/sCfHsr+HisVftQhh7TJcsyIVPgJT0U0+8dJhf+/5z4XYwzPO30Fl//k+xhjuPXWWzOp8Kcd9zRWr1rNE6sfJwzbpcJf/OIXZ0KEDz/8MFEUsXDhQlatWpXpiD3xxBM89NBD7LvvvjtzCYHpQRJrgb0Kfy8H1k92G2NM+nOzEOIKLH31f8AmIcRShyKWAtPXoKCDeUEhcD1FuqkV2YdN72KBP7XNwLVbJcaa//7No7zlOdPTkASeXCQxmXjPPTeuoTEUcdKLJ/cZs+wmPR5JBGORRIoaC4HrlG7qhCSUVuPqELIsJGMyimps4DpxTiLtpSFKpUKdxLbppqmmwKa0U/rWdCOJsZaxTTP8mPQNDvF3b38HYX2UIPA54IADePe7383JJ5/M6tWr+c4ll4CAyIMVp6/ggr+/gAsuuID169dTqVRYtGgRX/nKV7LjFWMSYFNO77nnHr7yla/w9a9/vU0qHLBS4XN7wBg+9alPce6553LRRRdxzDHH8Pq3/R1ozXNPO42brr+J5z7jZLq7u7n0W5Zh93yPD37yg5z7unPQSvHGN78xkwpPlWYPP/xwSqUSl156KUIIbrrpJi6++GKCIEBKyX/913+xcOHCnb6O0+EkbgcOFELsB6wDzgVePWabq4F3CCF+gKWihtzk3wVIY8yI+/104F8K+5wPXOx+XjUNY53Q0oprmDrdFLs8/jwFdtsT5Eeuvp/D9+zlZccu38HRdrbJpMBi4NZV/dPqJFKHEMggr+KdVu2mvJhuMnTTby+zAnxTdhKd6CagXEQScZp1lI9DGoMQdGxf2oluSgPMxuSTdxG1WrrJOQkHwv099kCPjKSDK5ygQ+B6G9lN2T299g7iB66CYDyS2JEOe1OxHEnM7HmOPOoYvn3ldeyzoIveapC9nlZat+6/H+UJnlgEy7qXMa8yb3qlwo2BDXcDZpxUePP++8FYQb+L//Wz1IMhFi2cR3epOxvjc1Y8h5c+4zUIKVi0V0+2b6lU4rvf/e64sZx33nmcd955k7w6k7eddhLGmEQI8Q7gWsADvmGMuV8I8Vb3/leAXwAvAB4BGsDfuN0XA1e4gIwP/I8x5hr33sXAD4UQfwusBl6+s2Pdlnlevlr0suymye0bp53TJpkC+4t7NzDYiKbfSUxQcW2UIhmxq1ABtKLpTXFMqZKyV86cxEwV00135tiWkZCRlNrpUCcxDkm4a6sKgWZpNLXAa1dYDRVX/fsf6O1ZPA5VxW1pqOPrV7QyKFdshQtW+osXE61+wm1QvB5FJDExXTQucL3xXuJwCIKuQlfBiWMa02m5FMaMnob0TulIG495bWYcVmfIZLQGk7artd/vWFkOg4H0vts1xERm05LnZoz5BdYRFF/7SuF3A7y9w36PAUdNcMw+4LTpGN9kTBYKiHy/PQV2+LrrQAjmrFjRcd84zZ2fZApsmOiMl94paw7A1e+CF30BXZmXK4qOoZvqv/sd0ZY+qCwAYKO5Fnj6zp/fWToJlrwSxO2vTYeZJEGUSgyVl/DIHwc4ZMmSaTv2D25bzYbhBrLU7tjSFXfJTAZJaI4LVrFW5cilPhiyadUwC5+yfEIkAXkmUTHGYbRBhfZCpkgiWLyY1gMPpBtQ2Dj7dVsCf+Pal6qIJM2WGZfdNDN002grQUqeNIG/dG7Wk3ESM+GxJjpmeu8YXbgIY2Q5TC4bvqs1rmZlOZx5gWz7XUiRTRT9l3yD/m9+a8J91Ti6aXtOQhEl0/DFb/gjPHg1rP9Dm6zDWLpJjYygRb4eaPLwzp+7YOkkWPJK416bDjNJgiiXWbfsZG65ftuhqU66VduyZqxI15ztges0JkEbklAdAtc10+Ib6oM8J7mpsL/dTho5jnorLhDiQhA7Na1yJ4G7p/zFizHNpo3PdKCb0owpmKDiOguQu/eSkETD636lqA223Oef2cD1hqEmm4ZDdx5DfzSzKqdZy9ZOt2KazTST8+8EwZdiirzIkATjkUTboXado5h1Es68ApLwfIkQ+Xer6qPoZnPCffMgpkMg21iJGWN2CknUb76ZeJObKFWc/SwqRY51EiaM0DJ3EsZMr2BYihrKXnnca9NhKZLQ0ifZjnNtDIVTOradpLcVkxDtSKKo3eSsTIyHpluP5vsn6SQkx12LIpKIO2QdaaVRYYpO85gEYKuvOwSu2x3P+GvUdFXUDZfBh4qoDQv+3+2GfR4esi9ldNPMIAltyKvMhcagCNXUvq+p2LaQRD7pzmR8JCO8xrycX9/MSbk6iTReYoxBFBYnu5JymnUSzjy/EJPwpS1cSVcio3VMozHhvpmTENLSA9tYRUeuMUyc7NiDuObv3s7Ad79j/0jcA6bCMUii/dgmCjHSx5PpAzG9D2a6Ag9kHhycblkOUSqhhYeKt/201Aen1ls7ViZ7UsemocJ4JBF3QBKBm7R9k5+7iCTGoqq4I5IonFsbVJQG6wWyWsabYwOXenSUTv0k4raspfHXPozGxD5UhFBuFZu1X53ZwLXBkGjdXl0+gytk7WbWjh9nTEHfpNUVjGb18GpaySQWWmMcUfZyRyRh6ab+RsRDG0fGdanblYTTrJNw1oYkAosk0mdNj24bSRSRgxFimxXXoZvMdwRJGK0xrRZqaNi+kK7CxiCJcYHrMEQLH1/abcQ0O4mdRRKX3b6ac7/6+47vGWMgjhGlACN9lDLbfKDrO4QkzLgxp4FrH0HVCPyqjTcpF39qRfkk4bsU0qKTyJAE45FEJydB4XYw2qCinMKUMkZ22awXNVrvSDcV0UOniumsX0WBbiI9zBjKa0cC12se6Ofar9+3zW2MKY5t5jOcJhOTSKfhyRZpRipiJBphdKBFq76dZk0TVZa3IYmiIzBEjmWwYy4iiVm6aZfbOLpJWs9utEbX69txEoWVkfAmWLpYC9MMpB1xEi7jJZNnSOmmZNtIQrUijPTwhMu5J5nWmEF6rHKUo62pOIn71w/zh9WDnd90Dlc6ugnYZhOWxtBUkYQGMT4mUUQK87Qg6LIoKQ1crx1el72fIomg6CS2FZPoQDcVV+9KmcwZGQSyJJBOdE7XR3O6SQYFJ1E4Zhyz4Z/+mXDlyrZjQiEFVkWIxE1CSZrd5P7cARS49uEBHrlj8zbl0o0x2YQtnoS1sTHwtf/4DKeedOw4qfCnnXACJ77sZZz00pdx4n4n8ql3fQAdRduVCj/h2BN46Skv5fnPP4OwMT5LsE0q/NvfSUfSJhX+qvPPJ4rj7Jp88CPv4+RnPoNnH/9s7rn7D+51jTACpRSnveBZvOisXEPq8ssv57DDDkNKyR13ZJqos1LhM23tTkLYzEMNutEEY9Db0kAZ5yS2hSTse9EO0E2pk1CpPENGN0WZkyhVvHExicQFQT0TAyU8JKPxKHNKc6Y8hk6W1UlsfhCqtl/vVJxQGOsJnWaKykSpnBUrJrHOCh7HWn0wRxLGmO0qYdpJuhOSyL/TqhHIuQK25jGJ4sfz0+wuk68s00lZGG98TKJIDaUNq8Y0HTKxAgLwJDIAUbJOykRRvhL1SpnDaLufBgcYvPxySk/Zn/KBB7rx5HUy9sQhpHRTiiTSwPUOIIliRb+Unb+btsVwmt05gyvk2279Pf93w3X87MbfceDSeW1S4brRIHzsMe57+GHOfsff8fbzzmPN449vVyp8xYtWsHZkLYuaezEWIoyTCn/a0zjr6d9i3uKeNqnwN7/+9XzrJz/hza98JTf++tesWvUo//fbm3nwsXu48B//nkuvvD6jyr72zS9z4AEHEyb5Auzwww/nJz/5CW95y1vazr9bS4X/Jdg4ukkK26g+nZDjGBNPAC+LVIGQ2yzCy+imHXESoZ0As8pbFWU/U66+3BWMQxLa1QFI7X4aj8Hm0JTPP5FldRKFB34qSKKVKLSZoAjMZY6JUgkzCSRRpJsmUwwZK43YDpIAuDO50W6fOuDCELwsJpHfH2mcqlNMoh1JdM5uStzn9rskPfsKhO+cRJzkMQm/lP1edLLGod7i/ZrFIjIkESLdRxFZ+9UdD1zrQlvXCbdp+2vm6aZNGzcyd/58SiWbdVeUCjfG0ApD3nDhhfzLxz7E0kWLJiUVnlXPG+urW3F+n4+TCj/tVK7535sxWrdJhZ/38pfzM1e0d9311/Dyc16FEJJjTziW4aEhtmzaiDGGTes3cv2vr+U1576ubQyHHHIIBx988LjPu9tKhf+lmBcUAteeC1xrk1M7gG428YJg3L5ijJPYJpKItx+TMMYw8qtf0XPKKYjC+cbRTSmSKNBNla6A5nA75ZK4IKhULRDWSWxpDLJ3715Mh2V1EsWq4e0gif56xPwu+/DmFJzBH7sIddXWolRCxymSmPj61oeKlI9hgkVtZmOzm1L0MVbjamP5MZ7KSYRpamqBS86QBIXAtYtJyA7ZTe3FdGNoIKzDSCddvxsW7qNp+qnCcJLTTV65Y0xCpVpiUfu1sC+mG8UZ3STShlQ7kQKbbENAcuMnPkHrwT8hC30qhNAgYoZlQFhInZ6slQ95Kks++MFtbnPyqafx6U9+nFNOOIrnn3F6u1S4MXzoc5/jpGOO4fQVp8IQHHX44duVCu/6ly4SnXDYAUfypS9dwua+BgcvsUkF46TC91zGuo2b6esfaJMK33PJEta7RkEbN1qp8DRwvWTpMjZv3IA5eB4f/6eP888f+BdGR0e3G7k2SoGU3HbbbbulVPhfhKVIQnoCIQVCWng81kl0tGLwSXjbDIK1JkE3RY8+yrp3vouRgqIkgB4XkygiCbear/kksW6bdBL3cMrYUmbSSLY2BiY8/1Qtq5MoIoltOMo7nxjg2I9dzyObbY58RsF1QhLJeCTRSZsqtWIK7GTaiRbpJsg/y9h9Za+dpOO0Wt0UkCeKv12yB5tKhXvF3QMdU2ALiQ1plltb2+pi+1IMqBCRPuzFOokC3dSGJFoOSURFJJEmLTiHlIRIRzeNDVzviJPIOh/uYNbeTFhXrZtf/uz/+Phn/nO8VPi113LjLbdw8QUXZGmonpTblQq/7ubr+PH//pgvf+Hr9qspPOsdpcIR4xCt0ToPmHfoay2E4NpfXseChQs46ohjJvVZw8ceI16zZreVCv+LsNRJZLSTsHSTGik8+BOkwQojkDpGy8Dy5ttwEpMJXKfnUVvb+zClD73q5CSS3EmAXdkFjrdXmZNoQskiiYHWNNJNaeB6knTTvWsHMQYe21LngD16MgquY6Wwo9hkpYJuObppGxNRc7RA+UyCW4+VBtnuJDw8tDIYYbNjQwyVHrtaVLFNTZQFJyFNzG3VCkvL+SKiWCcxLgW2UOsRd4hJaKXzRlYGSCLw7Gc3icqRhF/KHEbU5iQ6IIkxdJanIqTzd3JM29MdqbhO6c5O13zJBz+I0ob71+f3nJAtZKmPrvJc9uzZc8rnm4yZRNMlPZ5+0rN49Uue3yYV/nf/8A9c9rnPUatWaWYJV2a7UuFt97Vpz1HpKBV+7MEsXDC3TSp83bp1ViocWLpkGevWr+NpPA1jNBvXr2fR4iVc8T8/5obrbuC4Xx1BK2wxWh/hta99bUfNJrAIU8tK9vfuJhX+F2FjnYTBcMVd69i0MZ+ozQRIQhiBdBO2pZu24SQmgyTcQz6yaayTSGMSo3YFUghcp1k35TQLpxC8TtMpvdg6n9RJtGLFis/9hvMuuZW7Vo9HFhuHWjy0Ma+I/eStn+S6x68bt10nuqn4MG1d215V+3ifHcfWUXvNJnIS6x4e4NLPrCQs9SJrtaxfx7aQhIp1Vj0/aSdRYMuz3gpKox0FOeAZtNtGKHtsYXIeS6a5pCLJJmNViElsq+I6GUc3aYzKkYQxWCQRpE6iiCRyuqntfkqdRNzZYWqHJNJmSmngWk1L4LrzvuNW2Zks0czFJB5Z+TCPrXo0O3dRKvztb34zRx9yiB2KG8K6SUiFj1X01SZPyT7jjDO49tpreWzDY1Yq/IYbOeM5T0cIOPXUU7n88svZMhLyncsv5/+dZhWHzljxfC7/yffBwO233k73nDksWryECz/8AX535y3c8bt7+e///AannHLqhA4CLN304OMrd1up8L8Iy5yEm2ASbQhjxdZNA6Q5QBOnwUo8HZHQZQPX21iJ5RPixA/Hmk3DeMD61RvZu/B6tjJUCtNqMVyv0wsMjdRRPS4mURtPyaSyIV6YO4nB1jBbR0NWbh5l5eZRyr7H189vX3F8/vqHuWv1ANe/x/K4P330p0Q64vR9T2/brhPdlL62+YlhLv/kHbzs/cexeD97JVdttYH3raN2MkuDf/GYauqHb99E2NT0zz+EJV01jJMW2VZMQiWaUtVHxXpSvTNiZaBkkPjoQmqwVgbjS4gUg1IT0560IAvrq1QqHKFItKEkRTZZSjy00awdaPC9W1fz3tMP7hi4Ti+d5xxN1u0QAUmI8Lz0A+ZOwi9BONp2HADClG7qEJPAOQkVIRMrBiG0tumpaeC62MgoUgxsqLPHPtvOhNtevxJjbAMnA8TCIMXOB67Xja6jO+imt9zb8f3GyCj/+MELGBgZolYptUmFP7FqVdZdTkk4/cSn89Z3/f12pcIr3RWMMfi6xC+u/jX3P3QvX/jwd7nkkkuYP38+b3/v2zn1macSyIB/vvAC5s/rBQOf+tSneMUrX8n7P/AhjjvkYF7/wQ+CMTzv1NP59Y038MxnnUClu8ynv/A1ex3HFNMVL9MVV1zBO9/5TrZs2cILX/hCjj7qKK783Oe45c67eO1b3rlbSoX/2VsjbvB4fRWQV14rY1mItphEo91J6HqdZGAAgUS6mgUjvIxgHrjsh/SseB7+/PnZPsViuolSNMNWSA1guJ0SanvoR0cZGW3QC4w26gW6qROSUOCBH9rJWWrJUDREq5AltG5wvAMcCWNGC8HGlmqNW0nBeCRR9srZZJvmkhezjh7va3cSnQoMjTGsvq8PgMHeAxDVvE5iIiRh3OQalD1ao/GkkYQQGkEJSApIwqACgQ8MSDPOSRSRhOdQhpF5NXF6bmEkiUm44cHNfPl/H+W8k/Zpr47O6hc0IPGJ0CqfsI1T9UllwUxSDFx3jkkQjaeb2qTIlXZIwr7mK9tTIr1cRSTx0O838NvLVvK3n302perE04XaTnaTwdCjBVrAgDBIYfHbzqTADofDCMSETuKII4/h5z+5nhEPnrI8d3LGGJKBAeJ1ttZlqAa9DTCLFm9XKvxP/X9CK8PCxp5oAYcddQwvO/M52XavOO8VnP3qszlo3kFQ3wpDa8BJhf/6/27m8b46BzS24Pk+ulFHCMnF//pZMDGqNkRT7MFomLRdl2c+/dm84Kx8YfaSl7yEl7zkJfnniWNaDz3EK1/xUt729xdM+Tpuz2bpJuDRwUf59F2fAnJEodPHs15oH9ksxCRu+xp9n3wPq17xSgQe0klkG+lZae6+PjZ++MMMX3MNRQsLq+CJMpxSuklsw0mo0VESF4g2SXvgGsYiCZcpkwWuPYajkWwFv7S3wtqB8fGWKDF5gxytiHXcMSA9NibRFXTlk226Og3zyWztgHVIuZMYP9H1b6gzOhAiJQzMPQBZrWU9xCeKSWRSGmWv7e9tWRpEFnhtn0Urg/bg2J5L2aNyK7FpzxgThZiEMHDaw6/DixbmIntjUmDTax0lujOScC95IkInSV78lp3HbZeo9sB1RjcVPqsLVrYjiTHpvSrCd9lNnrY0iu4Qk2iMxGhttltdvD26SRvLMKXUjpgGuslgtp1Fl0mSdzhH4bVOQeTOhzMoraiOqddsi/cYPU4XKv2ZVX5rldGH6dmlhqAVF/YYgyS2Na40EcLbTirfDtqsk8CqlyrhKBlHNyl3UxedhBnYAJecAaNb4K5LUY/9kWRg0O6XOglhtZDTB7T4oAK0OlTbjrU4tPt4I8Ntr+uwkLkzWkfH47Wbqj0urbSZwMgmqPdl1buek/EQxmckGs4mrgP26GaklTDUbJ8IIpVPaKkQ27aQROA+Ts2vZc4krUZPncTagWYWIN0y4pxEh2D+6vv7AXjqAdCqLqLl92RKthMhifQapE5CTYpuck7C+G2fRSuDEAkndV3J3sEqFApN7iAl+QOp/W4O7DuWcuOgvB1pmk2UOYkcLRU/Z5SlptqfHgkmSTI/kEqFp7UcJonbkUSHimvSe68QkzBhO/VkVIjnvkpP20WA6pDdFDtBwLS170S2/ZiEcxLub7mTxXSpCN62nERR4XXceTqI7G2vriYxCZ6GxYPt+xV300bnjm+MLEd6fYXWCJeIkDkoYbOgcuHYdoG/zn7O2NiZchmA28v33kGbFichhDhTCPGQEOIRIcSFHd4XQoj/cO/fI4R4mnt9LyHEjUKIB4UQ9wsh/r6wz0eEEOuEEHe7fy+YjrF2ssALUC7VI0USWZexxihIhy42PQprboHN90NUR0dx1kOiPXCtcu+etD9cYaxY0Qg4PPQmDF4nDkl4I2ORRCEQWR/NnMQaNUrLOZCe+TbDoTkcwU/eyIb/uZiHKjbW4LkxyqSLejycTVxPWWSLh9YNtFNOcaIzR5Y5CTN+skjTPQ+NIl4652COW3LcOCSRTjKPu3jEfnPywHVxlZ3a4OYG1Z6AfZfY8/ZFPTmSmCAmMdZJTI5uSj/PWCShEdj3qoQonWBEcWLJH8hsxadLhcC1i0m4FNg09TmMNWGHiuusiFpEqDjJWw64R1SkDkoVkIRf7kg3yXA8kmhTBdCGJAkpFZxEopOOdRKRc+5RcztOIs6vWyczzt2l097OIgmTrc63hSTcuVwWkjaaKM0ILMy6WXLbdmp7lFZ4mkyZN7WiNlQbksiO58aqFXuJzfbL9j13Edr1mdLPZX9uWwU2DhVb145mhZdid0USQggP+BLwfOBQ4FVCiEPHbPZ84ED3783Al93rCfCPxphDgJOAt4/Z9/PGmKPdv7amRtNpJVlAEn4euJaAaDTwXEwhS4ENRyGqY6IkbzRkUifh2RVBqs0ypko7TDSHRB77JHJcNo+JInSzSeJWff7oyLj3U9Ojo5gkJAHeFTzKHzfeC0D3fCuy1xiOoL6VR9btwbC/iKVbbqdndA0AIummnoy4XgoWScD4uERcWPWmqpdj6aYv3f0lbt14KwA1rfnIvOOYV57XRtsAxC2736qtdS7wL+PG6NV0j6zKrgm002861ni+pCod2jCV7FonE1RcpxPz1JyEQzxu0k8/n1YG6RxiFy2USdCFVFnR9ui4iVxXswm2iCSUVoUiStUxBTZDEiLGKFVozJOexwn+xcXsps7aTSJDEoWYxBiF21jF7U7C5HRTmw6U+97C5rYr6CeLJNJPI9LA9RSQhNE6+xxZr4htIon82K2kxYN9D7JyYGWGQvLt0jFuB0noxDmU7TiJMTRT+t3KpEWvcR0ifT/rFWJfsOrRbUiiTQV2/NjSNOt00STGVaJOj00HkjgBeMQY85gxJgJ+AJw9ZpuzgW8ba7cAc4UQS40xG4wxdwEYY0aAB4GZSZrehpW8Uo4kghxJCASiUcdftAgoOImobpFErLJgqjBFukllCMLEY5BEK6GMwEOMQxKbPvVp1rzlrcSuqtdvNdqDj2NiEiQRg56kJQytKET6gkotQEpBYyRyldiGQDU5YvB6PGUn+mMfUzSSPCaRIomxcYlIaRLt+gG7fVWiM+oI4NL7L+Xax6+1187YayOFLCAJRyW5yabr8et4h29F0+bFG2jFqmPGl0qsk5CxdVyxyCvPJ3YSLvZSmoKTSGkxPT4mId3E3CUilBmDJLCy8DYt11FCupL3iU6zm5x2UxFJtKvApts5GQ4RoROVxyoyKWn3tyrUSXhl8n4S9jglXyIcktDFe6dwLaJYEat2JBElcccU2HjKSKI9QJ7ur02OJKRon/y0NtuUWkkt2bSJ6PHHs/3mNZcQhJWO2+pC1zcBbG5uGvPeeCexPaVVZRSireVoerx8G2NMIRTRHovQWoN2+/o+RhadjW1NkDNUhePYF8ZZhjrSBYk3M3lI0+Ek9gTWFP5ey/iJfrvbCCH2BY4Bbi28/A5HT31DCDFvGsba0UqyhB6DJGJtb+onyicyMO8gRBBgmq56MRy2SCJWEyAJndFNY5FEVE/F9sYHruP164k3bCApOoOhnHIyUYgWEoONSRgV0e8oGJ2YTL222uOkOVSEUiB0wn0ND+kmxKc/OkpLNTIksXxelUogx9FNUWHyTummPe4+gp//1x/zMeuYZmL3kxiIm/jX7Mc+W46wY85iEvb6Lu6/Pdu3mybrC+il2GNDJQYvkEgnyR2b3ElMNKFkdFMldRKTj0kYbb/3tfcO8fi9W9vopi7Zsk5vTBzRCImSHsKtCIWq5DGJlG6iPXAdqvbAdaq4GrjvxiOhHjUJU4Vfk9JNbtGRxO0psCnd5I7ZVfLwovF1EkW+vRnZJIQgdRIKvnbTo4WYRBFJOCc0gZO49erH2LRqOJPlKMaBGsMRg5saTk3Z8fHAvFpAOusZY6gPhgxsmrhfS/YZoijXLzMaT/sI1Xn1PBgOkmqhC9oR8FgnkQLE7cUktNHIMXO3YAySQLc1D4I8FmGMzhmoMUjCuP9Muhhwi9TMEXSMSaTjdkkSu7GT6BSCH/uRtrmNEKIb+DHwD8aYNFr7ZeApwNHABuCzHU8uxJuFEHcIIe4oKjZOxdqQhC8IExvEkwb6ug+lv7w3olbL6yTqWwGr1JkqkxoKSELpDEGYMTGJZNT+XUKPQxImDDFRhCoEGZOBgfz9KOKWEz7Muj2fgx4dRaiQfs8hH7fyBqjOKeVIQgmEjhko9yDchLJpTo3EhFmmVSXw2HNuNcs6Sq3YMzmlm/x6NWvsY4wh0QlNp1DpASZqINZ0s2hkr7bc+5TblmEejO8RzQLFpblv4DZGf3sTGzdsoRUm9vNELYSOiXU+GWwPSUyWbtr8mc/w2tstqtGObnroV1v5w3Wr0drgOS2mLiJHN435voSH9nzSeIbQuZNQRbrJ5HTTREgiFQn0ROwcl/sM6SOaxoISlaGHdu0me8xayUfGadJEu5MQbttWKyHRMSXnyDwNm4brHVVgo4xu6pCwkGju+MXjPHrX5qyqvx1JuOCyMnksAFjaWyVzEtj3tdId6R5jDFtGQhKlMcouvrLObQiKkjhFs9SQ5PNf/DfOeN5JvPBZL+Slp7yU2393O8c97TiOO+00TnzZyzjxZS9j72NP4qLPfQ6M2aZU+NFPPZoXnvEynnHO2bzwnLzfvVaK1sMrUY0GV37/Sl5wwgs46KCD+Nb/XAZYWfRVq1Zx5hln8tRTzuK8Cy4g1hojJT+68oeccuYzOOXMZ/LCV7yWB++/J7suv7nxRp753OM48TlH85nPfTo7X39/PytWrODIow/l5a89m/7+foyAH/7g8kwq/Oijj0ZKyd13393x+kzFpsP1rAWKSnHLgfWT3UYIEWAdxPeMMT9JNzDGZPhQCPE14GedTm6M+SrwVYDjjjtuh6JgbdlNvqRvNMKIwsUplZDVai4XProRsKvFNJhqKASujbZFT4xHEvXRTcyjxD5sHe8kosjGJYpIYnAw+z1qxbSqC2nWFqHro0gdMxC48yfgO6qsNqdk+ypI6ySkTthS7c2chMEjMRFNV0tRLXnsOa/WISaRc9QpkhDKy6qPlVF0NQ2tUhM8YVdZURMQeMZHGTUuJuHHw2z1FrNQbaKHRoZevK6H+f593+SMf9f89ORXIeY/h/3n1dDNFp5OiJN8MlAT9LFOV+/BJOmmxh/u5pDN9lZVysMDwrqiHGhLN/n2O6yJEG0SzJiGyCmSSOMGUlcz55DKaoixKbCqPXCdIoCA1ElEDgG5CuuMyorA98fXSYypuK6WPGSHOgmMVQFWskozUtRUlCOJNHDdKbtpG3RT+locKRcPEll1P+Qcf5IotrbWMZ+l9vU0H9bQhjK0Nnhe+6QfJpoNQ008KehK0YBSBW2szk5Ca82dd97O9Tdcy09//htYMED/1n5aUYtb7rgFf8sASX8/9z38MC95u5UKX7d+/Talwj/8iQ9z+jNPYG6jQqNmZTUEWIXoKGTr+vV8+TNf5rLrL+Og+QdxwrFP48XPOZY5c+fy3gvex1v+9u94w5kn8LYPfIxvXHop559xJvvstQ9X/fDn9M6Zx43Xf48Pv/cf+O7VN5CohIs+9EF+8L0fs9fifXj+S57Ly15xDoceeigXX3wxp512Gu/80bv55Cc+yee/9EU+9s638erXvJo3nP8GAO69917OPvtsjj766I7XZyo2HUjiduBAIcR+QogScC5w9ZhtrgZe57KcTgKGjDEbhK0kuwR40BjzueIOQoilhT9fAmy77dVOmC99jGdvOs+XbL3/Iea2hi3HDhCUnXaQSzkd2USMcxJirJPw7IonKdADzrY2t/L46E/tITHjAtfawWldFGYbGOSh/of4xK2fIHLBQ1OuokZHkToqIAmD9HMn0SwgCaliRoIa73UV1b6jMOouO6riS5b1VtgwZJ3gH9cMEhdokaiAJETi5RO/jvnUNxVn3+JWpBhUlMqR+zaINya7qRSPMFLaA4OgRzQz9CK8JrUQMAY1Okql2Y83+AgmbCF1TBTlE9fkkcS26SYThlTTWhOHJOK6Jomsc8uRRAttFFqM+b6kh/I80sdIqipJ4kQYs1iDcxJZTELltJqBkvssJed4PRHbeEZKY6YgPLEif0YlhVSogGJ2kxBQ9iVehiSKgWuDdAik1YqI0eOym9LDtgeuJ6ab0kLJqJVkzqyIgvNML9W24rfOI0cSqTMxHZx6XpFu8qB1kgfZMaIzAtGwectG5s9fQFfZRxvDwkUL2WPJHlkGUioV/tmLrFT4lq1btikVbozpSDel4772hl/x9Oc8nd55vcydN5eTn/MMfvG/N4PR3Pi/N/KiM89BG8lrzz6bq66+GiMExx97IvPmzgXg+KOOZNMGu2i5584/su+++7H3PvtQKpV42Tkv56of/xCAq666ivPPPx9j4JUvezU/v/YatARZoK++//3v86pXvWrcddkR22kkYYxJhBDvAK7FYuRvGGPuF0K81b3/FeAXwAuAR4AG8Ddu92cC5wH3CiHudq990GUyfVoIcTT2O3kcaO+wMc1WlOUIr/klC5uLGSx1AR4mKCFqVUzLUSWjm7hgj4W8Bi97mLUoBq61LXqinW4aaA1Qi+cANm2yE92k4xgVtyOJm9at4ft/+j5n18+325Wq6NFBklqJgXXvo9pzGYxFEiMRphSilETqmNjz2VxxtJB7YOtRE18KfE8yt1ZiqBmxYajJi//rd/zHuccU6KY8cC2Vh3Yr6jgO2WMIFg2l/DtoFzT1tA3YFovpjDFU9ShxeTnobnqSBvc59CJkTMV9bBmFVFUDr7EFHYR4JDvoJLbDMbda1FL9K+PhqwAVG8IwIkkUVeckqiJEoTogCQ8lJSk1JFUV0iywQgosQMshymKdxOnNgKMin3/vbeKjseSSnQClqwnJiulUZFMckyQno728n0SkDIEn8T2JF3euuE4LPsNWi63hgazd/x3s2f8ZPB3a7KYOdFOz6dKUGzEX//JPnHLwIk7af4E9p3MgYT2/x1VYpLjsz1uueIwN6wYI9CBgEwtaKkQbhRCCQA+DMfiBh5DtyCDRmjDW/MmXeGELjEFU72Xusi4Of9ZyhBEdC8+MMZzy7Ofy2S98mueccjzHn3I8L37piznixCNQRhEUpMJfeOqpoOGIpz51m1LhH/3QR/l8rYY0kgMPPtwpwQqM+6Dr1q9nybIl9pqokJ5li1i1aQt9A4PM7e3F931MJFm2dAnr1q3LYxJu6N/90RU869TnArBpw0bX+8J+F8uWLOaPt98AcZNNmzaxdOlSRgdaLN5jCVv6+lCi3UlcdtllGVW2szYtkQ43qf9izGtfKfxugLd32O8mOscrMMacNx1jm6z5vocRNvgb9vcjzCK6VAwyQFRryGoNPewE90Y3s7rHh0RkdFPqJLTwMFrlzqFANzWSBrWox/5hvHGB6yRSJNqDMEIh7Mp8cDCD/w+sGwYPTFBBj45S9/dA1I9gUf33GAVeycUkekroxBCaGsr4SJ0QSZ+WcRO4m3hG4yZVR1f1VgNiZXh8awNjYLAZZ+NLCnRTm5NwxX7p5O4ZUFEamLdIokg31SNFj6nTKvcidC+9zSZbXNU1Is4qWWUUWnqEENNqIo0iCguZT9txEo8PWme4XScRhlRTh2w8ykmXvS7NBkZ5eMaOrUbLJiaMqRExQpIU6CZPV7PalTwF1l7flkOUYWx7GAee4KjIPn4lY+kmiUaiMVpkCDWLSaRIIlEWSQgPpG9nYmNRacmTBFLgdwhcY0xW8Bm1QqJkH8LqMlqVBXhq/Zg6iXz1riNLI20drPOVR/uoh0nmJFIk0ejLU7V1gW5KFwgpu5SPZcwXYfIfYyeD9no0k72YBnTTxIDiBAkWYHV1dXP9z37D7bffyC/vuJ53veFd/P1Ff8/b3/x2rvn1r7nxllu46Qc/yOskhOKqn13FPX+4hxtuuIF3v/vd3HnnnZkK7D997J84+xnPoBpVaVatJlJZR1nSQ6IEckwqtU1tLcRpjAQhEEJk9RYCw003/5bv/egnXHL1z9x29moY4aR7UgkfXaTz8s9bRBK33nortVqNww8/nOmwWe0mZyVZIl4yyB77HMaGoSEEhqpOQILo6kZWqySbHVoY3URzziL8xBClq1ZRLKYzGc1UTIFtxI0MSWDGF9P9qfdkho/oxW/9kaZfpoxGDQ6ijKtj6G8RLAITlNAjIzDX3mTlpIpJBF7N/l2bY6uum3ouiSkhTUzkBSAjjNFIhyQacYuycxJznebTE05XKYxVIbspp5uk8rN6gWh4ECCf3CGnm1IkofLAdf9oxBzRIKz2gpnDPK+VVV0LkVBxaMGPI6SReEToVognFFGhynoigb80JnHnuiEWsX26SYchZZ3gKY/YeFSckzCRQCIxwn7mimnh6zplMwLkOlxjkYSnyyjXyyFDEm7aK8Yk4sRQLRQ++UYQoBEopLC0TyZmKHIkkcUktAHpkXVU0jZlNvAEvifw03uvDUmQIYk4ihDu0Y+DLnyNDcxndRI5+kun7U2b7QKlv5EfMxyx16e5ZRiwqajtSMIe52ln7k2fKdPbsqnkvYuqrGmtJ9SjCCFYVLdJDt3zygRdAb4UmabZhqEmW0ZCFnWXmbv2UQCCZcsY9QOiAdNRit2e3P7wPI+Tn/4MnnLawTztqKfxve98j5e/+OW84wMf4LJ//3dq1WrB98SMxCMTSoVrNJ5p7869sDlMGNhneo899uZPt/3Gbms0m9Zv4siTnsai+XMZHBoiSRKMkazdvIlly5ZlTuKBB+/jPRe+kx/995coz59LEMccXl3AVevX2Q8iYN36dSxbvAi0YvHixWzYsIHu0lw2bd7IogUL0CIv6vzBD34wbVQTzMpyZFbySmw97S4OOmEJDFv4W3arAVHtQlarhE03oemYphR4iiy7SWV0k+tx3SEFthE3qEXOSSDHyXI0ZTdhuRev1SCRHokfYAbXkww+AYCfZrx4JRtEdyuYclIFJbMaj6pzEg09F2WCDEkgY8A5CWNoxiFVhz56q9ZJpDLeYZLTIlFiCkjCRzuUFLuK8HRy98pz0HEek1C6QDe1EvpGm/TQwO+aB+U59Mpm5iSQMRV3qbw4AiPwiDCtJp7QxGEhPXYCJJE6j6ZJ0zG3jSRSqYpqCBiPSmydhEycREfqJAjRbhJv2194FkkUVrFxw9UobANJhEqzrKgiC/hYoUGJzaXPCgfHxiRSWQ7h5XSFSZ2EtJRTB7qJgpOIwojEpRTHQTdSQ6IVRmmWJzJvY1qoh2m5Ph2DBSfRHLALikjlnyVFksbkTkInnSQm8hTYPMBt+NPGkTZ5mHYBRLd/kgvgCURHJ2E0PPLoSh55/GHSFj8P3vsgy5Yv451veSdve93rMqnw1DZu2swf/5Cnd4+TCjeMK6aTxmSFEqc85zR++5vfMDQ4RF9/Hzf/782ccsozEELw7GeezE9/cSXGCL535VWcffbZICRr163h/De9ji99/qscuO9+gGaJHuCkQw5n1apVPLH6CaIo4sdX/oSzTn8OGM1ZZ53FJd+8hEjFXPaj/+H5p52BcY5Va83ll1/OueeeO+6a7KjNIglnJa9E7HLTq8ObELV8xU21iqxVEYUVbBMoJYLRNLtJ5kjCVlyPT4FtJDmSMMZv61AGllrQMsAPmyTSx5cGs/p2kkdCCMATjrmWPqrVylaDJVXFi0pUHBqoOf2mhupFmQBfJ8RegBCxzcMWHp62VagV36KU1EmkSKIZ5VW/sdK0RmIw4CkrqQ3QGrROIkMS1XmoYZclpm12UzpRJJFmoH8ATxhKXfMg7KGvtAW1aSPdVIhEHpMoqwjw8ESMbjbwSib1uUhpJoxJtNykVo02AHPG0U1hM2Hr6hH2PNiW3BgXP6lGMECOJFJTwsmjoK2TEK4wDIXEc3STxBR0nKLMSYyNSSSA5yquNcvjIpIA31gHIUUCWuYSJOmxlZMLT5TjFnz7z56MKHExCdmOJDKlYdcYCyAJI4wpIInYIoklg4bTR0vc4jLR0ow0oWNKUgKa/oLQXyt1EtrP5s0su6nAhRhlELJQE6Dz+uGi81CJDSg3IsXcmn0t77dR+M5Vel+5YLnS42cyI6g3RvnAR97LyNAQIpAcsP8BvOItL+f8s85nw6rVfP+KK7LNT3v60/mb817FRz76L7xj0zs6SoV/7KKP8cVaFwKJFj7XXPVrHrzvXr76kx/x9Q99gHlz5/Oed72Pc1eciyc93vqPb2Xu/LmgFB++6F94w5vP51Of+ShHHXoIf/u3f0tr01Y++x+fon+wn/df9I8IE6FLJe666nto3+cT//Ipznvtq9BKc96rXsNhBz8FjOLCCy/kRee8iEu+9g2WL9uLS7/wZYzLCvu///s/li9fzv7778902ayTADaPtKi3YMhRBdX6oOU904dQeIhqFaJ0koDESEBlonO00U3KZqHQjiTqYYNqvMAdYzzdpPAyJxFLj0BaocDEPdxSBtZJCB8VhkhjnUE5qRHEZcrdzklkSGIeigBRRBLCFgBWImiKFpXA4xdfvgc9N3USFkmMtPJx9z8+TPS9fTnggGORxqXAak19YJAKbiUOeNV56K1pcNzjrodW0duXF0mN9vfZ69szj9F6F+9fHPG9b34CCbz4LSdnTqKiYhLj44mEuNFkSIXgQjklf2KBv6bL1X/6qit5hNe1OYmtX/saDz5e5t6BvXjTv59sg/xupV2NwAQ+lbjcdrxE5K0flTCZk0hkTEnnTsIrOImkYS+GKqTAAkTKOok0JrFHIVzgI/CFRqCRfgAtrxCTEGzyPO4ZeJD9gpRuklZPLG3C1LeVJE4o+TZwHaTBeLCBbtcnPc1uSuKCk/C78EOLJLzEqQykgovO6ZbDQXTXfF69sJu7BvPvMxx2KdMFJKXjVObE/m0D8X6bam4xu6kob6K1AZGnC0OubVXs0WKzm/KPGCcK2r860HDUEcdw5ZU/o6QFsYCSV2ZreR3rR9czf1PTCmYWFmqhDz/8+Q9Z1r2Msfatb32LJ4afYN6GOtBFq2IXGk87/Ag+e8JJMNIPwKtfcR7PP/905nbNYWtzK9odf5+99+Paq26k0uxDliPK5TIt4POf+iJf+uzniZKAIBpia5ePH20iwud5p57Os1ecTI1uSjIG8wRozYIFi/je1d/DH6lRVlX8uEEkBwE45ZRTuOWWW8aNf2dslm4CNt77J978zXVUH7alGbIVITCZA9DaWKlq9/C0hKCUFsSKsUjC9bhOxiOJ+nCIQJLIJtr4uQIoLkgofLQMKIUtEumhhIQkRrmHWwo7+Wvpo1thlnZonUSFiutKl3ani7LAdUzk+SASDBojPEqJRRLVwGPz48PEfXZiSZHESKGPxLrbbK74/OYS94pEb3qA0o2foV5bjK+r9tXq/LzBkfG5+Yr/RN9zeXac0X77IHX1zmeN75OIfIroCZsZ3VTTLRQBHjFxvdHW5S7wzYRS4U3n2Hoe2QDAZbeuziaZkV/9ipEnNmG0IQ4T3vWd27NUUks3SapjkEQkC1lmAKmT8PIkhUSKNiSROKpkLJIIkzQLydJ4NZ1X03rG/pNCI4IyQufV5RrJt3t7+Mf114Dn57IcwmbWaQWPvugcDvjDb2zg2hOU4ihT0Mspp7x7oopilM7pJl+B0glz6oN2zO67H3Ap0ZVwEKE99nykySm5ugWt0YIzSsebIuhUi8opEXgmX49adsg5iYLz0ErjlTfSUrnyclazUaiYNkq1VUeHHWJUqTqGyXKfpKWLhMwrrmX79CcK4+5knSquEcIuCgtSI74OcnmXbDwm3z5lCdPAtXsvDuZQU6W2EY2ruM6KLr08o0uIcZ9lOm3WSQBVozh6dYvqYAMTx8hYI4xGS/sgGW2Q1SokVlulIUSWY649u41wq04jPFtxnaXAphytIdxkt6lXNqIptd3cJo5RMkBLn65whET6KCExSYJoJBz9qEZIu1zSeJgwZNQ5jZ5wLtJ4mZOQUiA9SEwZTYA0jm6SMUYYtJSUYwhVRDmQRC2FJwRPGVzLJ677LJUkZK/+W9lfrMczMPSopZWkzh90fd9VMNzHH456F3172OpTrzrPZm+4beeIUUyBTghdf4xy93zWjFFTOHbN1iy2UVMtlPFtzUCziS48loGv2xoqFS2s21Vu4PSeVm4cYbOLeSQbNhI5Hr5vKOKGP+YqMbXQAHlMIrVIRi7fCLQQKPe4qMKCIJEyl2ah6CScVEJaf+EcfRhr4kRTVjDissR8XEwCRd3I9tU1kodLgZ3wPJHLckib3aRCiR6tUxvYQuALfCEoqRjpcv3Twkzbh92OQcUxukA3edoWRh40+AgA80ZsFt+azXayLoeD+TXBZEWYUX1MYwVyuimbE6OcfgQ3aes8Oymd6KQn3MRvUCa2FdbGFJyEm26FhCRpy+yJEjVBX24DwjkJdx+2O4n2XCphyApFO5k22mo3tanACtvZr/Cd+TrIFjbZ3J7WgghJKiBczG6yv4g2JyTSQYmCY0rjbYWFkyEP9M+EzToJoDrHBSzDCDVs0zqFyKuptTaIqs3eMErQlCKrVk0diZCOi5a24jorpnN0U+OWWzjwP24DYLBmC2Zi9wDd/MhWwnrTHktIFiYDaAlKeJhEsfeDmgt/qPFwSEJ4EOVOYl7LpuOlTgKsNExiSigKgWsR24dUeM5JtKj4kjhUSANH9q/ioMG17NEY4E2b/oW3+1eyfyyz5VCWmQXoR/8PHQsSv4r25iC0QdYWoNzkI41Hrx9mchcAyahbIVZ6WeviGlt67JhPeLy/EJOI0Q5JmDBEFZxEyZ84JpG4plC+05ISwGAjxsQxyZYtxO76PbF5lEDnfE8lgopfopJ0tx0v9GJGvV5STBW7BzGReYOpWIxBEq52IM1uyvP388LESGmCxDDissR8YwsRBZqhuPhI2iK0+0tuceAJG5MwysUkJCpyTjlq0RvD/E2ugn2Oi31FsZ2ghJelwAbNPpSy31OUOYmEkpuIe11L1HWOOiw6iREvzDKcOinDpoqkxglDpnEQqT3r6IRx6Z2pE3Xpw35+nyEMYaJRRbVWbSd7Xa4x6s2lMEfSCBMe2jjS1vwnFUNKJbctkhB2Bd4KbMB8zMRqdZgmdhK2x0N7oq4Bq4nWhiRKWRqxThFdNvOLnJ1LnUSRO2uTGilkUo1BEtpovHT6FnKM45rYdqR/x6yTAGo9qZOIc0G9IL/oWlm6CUAngoaQOZJwcQspXV9h6Squ0z4FccLqB/q4+3d9tMoLUST0Vyx9o1tN/rRhkOu/+RHuu/GKzOEkumQXTEKCShCxXadI4SaLOESELepu0qtGlh+tdOUrfT+wSCLLbnKBay1yJxHpkK6CI1ya2Mlhz2QL3WaUBYzQVUACtbgnvybr70PHEoQk8cpUIpDVBSjsZ/C1T1W00IUJVKUqupVe1rgaBM89IEetGcnopjSrzBMxhGFWgwLge3rC7KbYOYk+ci2pwUZEsnUrGEPsnOrarQ1KKqfTahFU/dK4wHVDJgz5C0jcAxiZMU5CSBIpKIb2kkzDqB1J/Efwn4DtwtcKFYGCYeckPFcTYxKD3JjHQaRIEAhGXFW9loLVajnD9XJWJ6Gdk/CikL0HNAtWuiy01EnEcR4fcBP2osE/YVw8Ky7lSCKdpKsuprG5397TRSdxpHyUAYcgonD896BTBD0aM9oYRui8bsZO2U7kLs1OKjoJUqdqaEVJW6pzoEtE5bmooIqSJVujlNJ1wo5fjXEStvjROQljl+O+KlNq1Ox92gFJbGsSNUbbbYoTshBUdSujfjUaqb3M2RgjLPWVFUC6wUG2T5FKE0XHkGqXFEstdI4kUsRpEOgJ5Enax2/o6+ujUumsnDuRzQauyZ2EF8W5VlI5n9zWDza5u9VkKdZJNGVON8WBnbg9z6UdCt9+kQUkcd9N63n8kSpzu/ei6W+l6TSBCJuse+hOLmz+D+Lm/+Eu+W0AVOokjLQctBO3M57l/rW2mLTl6JP0ZglqBcjrG+KkihEeUifE0gMZI0VC4lUox4ZYRVSz+9SwKLZFUQdo2/t3nhjJpEm0nxTSd0EbDxMJDBLlV+wEX52PcrRCd8sjMK02JCGcoiuVuax1ooCBm0y7Is2chh2Mn/VWSBBxjPYHs2OUvImRhApDtPAI0WAsOtpabxI7+iQW9uFY39+gVChKqoaw0EuoxF1oGSK1/U6bQjHqz6c3tvn5kXN41XR1KDwSYdpSYFMhwwxJuElwubRkfjNSaLfNwf5DEB+WIQkSQzDUAuerfBETmZyjjqXH3d7T6fvDLTyjpFgoPFRsx+JFTUpaILSdgrwe69BNFGWyEamTmNdczzpj5SbiApJI03UrcYKOIoaGWlSBcjiQjSExAYMNl0o7nm1Cu+9m5LeP0H9owmjXMGHFIkiLYhVBUGJEDtjKZ1WmPxmkXPMJGwn10hDa9JNEq/FUzJaghwWtYZ4oz0XqGOl7tuAU0EIhjUfsNfHjJg8OLCZwPRUGB4bxtEfsxfi6bJ2EMCSlCD8sE6g6UmpEsZGXgOFWP83q+H7vAJtHN9Ic1sTBCEraeylI6vimhTIBUamOEgqJoFWpY5KY0aSXPtEiNCsRRuLTxPNalIYM9cERtAoo6SaRrLp7SrNZ90MkaQ3GhH6TClWkVtREH/gjsKnFxvpGBqIRhJYIo0j8JoNDHb6QMVapVFi+fPl2tyvarJMASso+BEEYEfbb301PGdyctq6/yep4lFfh6KZCTCJyVIAnQzQKLaWtuC6kwD70xCAlBAPzDqbl30fsFGdN2GTkT/fy2C/3QJy8bxbf0DJASIPSlqeNxVO59fhXEpbsg6/c1xaaYpALRKXI3RtC7RCSjomDGCEMZe8x+hYex4ED53Jfb0jVORitNHOitQAscaru8xjJisGSIKRaQBIGiYlt1WjiVWyGUKmXOLafwdMeJZptVEwQJ/yyt8YXr3ktUWRpPV8Z6n6FrqTFosE8kAsgifHiGFUazI/hWT0opTSe1w6EVRiiRIkgsRSAJyP++Y9nsW/lrQRA7NkHe13fICWVTw7V0LDYa1BJummVBqi1bIC+hWHEn5/VKqR0056xZAicwJ9FZgaNEklW9JcjCTvGiotZDTRiqm7Vd7J/CzdxGN0ywVMGjKFaz7UxfaHaAruRk4IuP7aVgQGY+2KPe/QLmCvugHgNvnFrTyHxelMkEWU0TOokhDIYF7hO/BxJpC1cA6V5/KUvZdnSs9Fyf6qtvnwMpsL6hwf48RVPECYSqSK0l9+HyiGJ+qPrefTxuZzym3fx2xWfQ8RlSq0tKIZYcPhRfHnJh6jHgxy48TSe/sSLOfMth3PTd+/jysO+wHBpAT++/NeMrKvwH894Kxf/7r/5/bM/R62xiXn7LmJNn51Q1/c8yrKRp9DVfwUn3vMrtl78CX7ct5zTj1nGym9ex9zGXB7YdyV791mpC2EUW5/5AAtuPoJD117B3OWDVP73DhrVRdx72Js49P4v8t5/mMcZcz/Dv5w9vlr5gi+/ns98YZiHjj2PzT0nAXDgystZUr+BEXkk9xz5d6ztfYhlQwdw8zGf558+/zi/PuU/OKR6Iw81T8TQzd7l/2PvuVdzyEfv4tuf/DojT+zP01Z/l7v2fq29x2TIaaPvwtzVw+3P+gw373MFZ/ovpbJ5Iy/vegvs/XTM3/ySV3/31fztHz6MaMwhiIZZv++VfOSfvzVuzNNhs3QTIJIRtDCUopj65s0APOQXpAa0YcTRKPWkQkNKSrF98KKSmxRlhBbaIQmT95NIEuJU20ZIYrE5U5w1UYto3Sowgk1qv4xu0jLAk8b2J9GCZuks6l3LSAIXjHRZV8UeCwCimq+wPc8QGuckTIKe+wAA83q/zMKtf2R+eIytk0hhsjL0NuxnXqTsynuuGM2m+LjUolrg7BU+xtFNyq9QDUF7NeJWOmH4VGmhkUgnjOcrxdd7e1k9soaNkaX1fA391V4A9nBMn3RFgtI1ckqzicA6CQDVIQ1WRyFKKoIEhNF0iSGUSdj44O/tcXw7uTwYfZGKn0/G1QgWmREqcRcjpXzV3NKa0WAhiRCceYfmqavte/56O2laJ2HRoxKKyG+RRIb6rbcRD7jYlpvkA5Hgk9Bfj6i5xjPdnr3Oc0SMFCDQzB1YmZ3fF3FbHUEkUocuUU3Byke7uDt4HY/v83xkNEIto6VKyJ40JjHeSSjtox3iS/wupJJoo0h7VwQKosefIGi1EDqiZ3QtS/o/y9LgfoTx6PvtRjY+NkRoygRxe/fEVP02amn8pGnvrsCixlISUkpColaC0gk1bSglVTSGuZ7NSOuKelkm1qATy80f0v+Eu9YeUamXyM8pwXowgkYz6uKF8X33sOcdw9x7w2pKSYDUMdUCrWiER8VY2jg2Aapsn5/hnr2pd+9JvfsptJIWV929vp26Anj8d0iXGKHLlSxTTEufeuxljrLpDyHxqA6EKK+MQBLrKsIVHEaiQmBsMWCSNiwb3JqdxtMBofbQ0tGBXoiRBu3uGcJRIh2R6ASRIipZyjW+ZsBmnQQgagtQPgSx4vFVdwFQ9ws3l1YMOSg+qrrakEQYBEgVUfIMWlgkgVYFWY4YrygpwZasd4WIQ8SgpSFUQSRNS5/At3kWRoOXPJEP1mi0c1hjnQSlnNv0pCLUdlIXOkEs/j8wghOSUWqNLUhsSmxgcicxp25h9nxtZ+s5oknguNUoaIfg2ngkyj6wiVfhqFWGvs9/jyi0yErgUxY2cF0O7AM1Z9UQr/lVPuntG8YECga67ITW7ZCbyGQuXGW3LDgJ6dJQHa0x8MMfsvHjn7DXMI5RIqGk7KpxvrCfI1y/Gi0kyjkJ3/iUxQBR0ENYmkM1goWqjm8ChkrD2bkiYxgqzSURsLTf0OUqtNNe4Vp4FkngoYUi8lokMYSPrESL1NG5jChsk6W+0ZCqm3+6pXU2srLadp4zGj8JiYVNFfZEjEDw1KarW0ipPzxMbHsOAWxcfDw1VWeOn04afk43xXGBbnLxEu1BMSXVq1knkV13gYljhAbphB1rrcfxS1aCJJmT33fGxbEAiyrSKn3t48duUvVGsvdLUYsoVCgSakZTUhViqekauceeJ57DXL0BndjrdmTfoxgERvpEpR4aUY5Mtdck8cLM+Yt77qdmBAsGHyZQNvW7krQH18uJdSiJKKHLqaO0jqNZWwo6ZKgZ88e1g237JX/4LoHTD1PlMp5TINDSp7uJjZMAibSf1W9CHNTctaiSkjaRqVAiJlaGRHqWQosKcSgkI5RRXtkdL0J4llWwBxhhNLLXPHUSyivhTaLB1o7arJMAqM13TkLzp7W3owQkhX7GWgwy4JxEU3e1ZTfFgRXQC6TGCO0E/ozNQsFKRZQ1mVKkUFtQItXob1Ju2AlB1PNJWMuAkqdB2oBVsVdvSY+ghY9BkBTy6UOvQUzOSbaSkJZzElInxIGid2Rv9iZBmBiBh5Ax5XTiCZv0OMG2blXP4h01YpAQefmNDGDwUIl9MJRX4dn3aVq/u5PmsH1gEdZJGDxK0rZWFa2ABZtyJ3GMkzkZ7qq1HTtFSsIJ6iVe/rkCmRaE2Ws4+r+/YcipXaokRsmEUmIQRlF1fKHpG8kmErApimXd4k8Hv4oHnvo6aiHMiyxvnoh80vOVYnNQI0Hg69xppStyIzyUsJlDWigSGRNGmlWrt2TaSymS0AKWliPqkaLmHHPgCqDCyjrq0mbO+ImmIe63r+sqAskHHejJkITxIYFUvaJVXYinA6qhvZeULCF7t4EkjJ8V0wHc/IxP8dStSzJq0HOTjzASP5VjMWV8qRF4hAU1XK3z6+WpMBd0NAG+izspMeCOG1GJQpJQkxhlkYSqEApFmUG0iOmKeolFgnJO4pD+J1yLWEBIRgbyBYP06iReE8/Yib/7MXuh/LiJpwM8HVMd4yRKTTv5xqKEDm0CSeok6l2L8bT9vL95qL2BWRiNUHUp2rpUxtORXbBJ32pfOSQhhHUSpVBmx21FXRnSiJ2TCBNFXSdIFWd9XlKri3J2vNiLYAySqMcuS1Dn2U0LdPszNJ026yQAghoqMASxQY40qFfSzAhnRjEk7Qqzpatt2U1JIJE6IvClpZukx3BzkKsftiX/oQ4QCOLGE/SMrKYUr0O7ia6vf5h5Dq57jdxJKBlQ8pTNatACQ+4Mqm6Vr6WHKiCJll/PRPgAhlsNopRu0gmRKHNE/55ITyO11ZgVJATuY6qhzdm+MtH8QR8IpE5CEHrt7SX7jngLInKyCH6Zij6APx7xVuojKSXlUSYkwqNPtJizqEIzWEypBQfNO4ivn/x5Dlp9LsM9e7NH16a2Y6eV7unKN3J0kzAK3ynZptXAamgIPTyMGh1FKYUWCYECaRQ+MV3hXEqDreyBBQvpl/oN4qCbsDKPSgTdLTvZSVWc9BRDnkcsfTyHTuzruZMIvAgjfLRUKBkz3FDccNeqLH1a4rFwdDmbm09jcdnJvjgnMTTgIXSMr3yb9Wg0vtbUzdXsue437F+9wx7D+LbdrZsnjEMS9YJ8elQ9nLUjdjLWXoDszgPXWWFf2qCoERA02lHo0Vv2y+NHhYSIdMXsxx6+pxBKIl1RpN1msHBdo6zDXCxKBNre04nbRqqIUtwkaWgSrS2SSKqEQmFaQ7SCIZ75YA97bDBETj+rkkSZw83MfQ/7rWviqdxJSNfK1MQGIUqWbhpTaFequyp1r4JydSFxYJ+Tem0ph62NOHroT/xq5QO86bo3senyH5AMDDD86GbOudnFm4IyUidInWBc7/XUCXjGPp+lKMgWJk2VJ3wkpkJZxESJpqFipI4QhSQKgJYoZUii2goxSYhKHUI0ymjs7lHt4WG/n73C9s85nTbrJACEQPmCUmIoNyLqVaDgJASGaJ5b3ZlKe3aTb1NMK7VuSzcJj8cHH2PLiO1eF7qMGt1Yw/F3foreuJXRTfd1/Y5AN3h0v7MoxFEdklA2n9oALtXVS5pgbFDZCB9dQBKtoM4T/UP86M61tGJFI2qh07wEkzD8yEc5PG7YzMmsglvZ6lwgLmQMqUTwoNkbgP3FRkp6lJZodxIPLj4b39FoRnj0LziCvgVHEOMmYyFReAyIgChKMF3D1GtLKbcM3UE3h815OkP1FWxZeCS16iBJqojtiSytOH14It85Ca0QbhLPnITLRovXr8cojZIKP7HbBslCXnvXh9EcRFLJH1RfBxyj7kMLj8ivUQ0NZZflUopyJxGohIYnSIIKnrZxDgCpcwmWhd6AbWPqkIQwEhq5sxZGctT65/LIwPnsUbIPdFULhGxwx6hb7UZWkys9flerycErf0hV2gknokw3kqggHy4SaDQKlKi3kO7Q3ifruhfjOe0eiyRSiRCF0IrRzTW80M+oJICN1a2ZWKUmjyv5Lh3Wbyk8qSGSLFq7Kr9XHBoC6ySUMphWi8QrExhHN7mJU3oh1eZWdAJ+3ENNGwJVIZQJrfogoRyipHtZtEmgCvUi6f2QnSeyiOGQx1rUWk0EdjLO0GIsUdLv6CRkU2bbbi01SWSOJBq1PXj7zwz/9OB3eWLkXh56+Pf0/9NHGf75L6j/oZ+D10Jzzyq6WkXoxMb63NhSuqnsFnGVuJojCdHuJEokhIltRCV1ghyDJFqilB3vJb9rUn3gURIjee+iBdRVSL01bFN8tUfJWFRxePNOiDtnZe2szToJZ8qXBDGUmwlR2bRVXkoMcdl+AQ0TtMckfMsrzu2ZjxEaIyRdXhXf7Z6mtnkOIs4JDWffbB+82G9RF3N5Yp8zGO4+ODuflgFlmdhqUSMwlOiqb+Dkmy5gdbAu20YmQVaBGfoNfnn/Gt73oz/SiBSSYtvUmK6Sz15ii1MFsO/5GCote1MXUblOBI+YPQHYh614RIyY9gDlhv4GQSHW0qrYgr6UhwVICFBRicWDCaWND9OqLqQUl6h5lYw2iII5lPxhRtzzXe8K8tqTtEJYxtnfJrHjSMXn0rqWZMMGtLFqvJ4WCKOQyQIEElU6ALVs72xcng7oiQcx0ifxa1Qj8LSrOQlzZ+grTSQlSVDFLyCJjG6SHgv9AbRzEso5ibLrTmdQSCOdTEOJRSUnKGigGYyysmw/UykJbMWuoxW7m4AUCPc9RaZMzUCcTeKO+ixQlEJUES7b7T9OfBlrXbC4iCQSqRBGYfCIKh4bejfSrTa6ayIymk+JNK7kZXRTECaMeAotAqQ2dFUjFm2+i1DaQLskRmL7h+jRUZRXQTq6TzkKBk9RbVoapydcSE3bmEQkFQPDfURihLA0Bz8UUFhcJ/PzrDqAxKxyh2vhqxaCCn09BSeRWKFMqWMqY6rzRcFJ/HxxCS0hdvsZGRCwkM3dJ3Pu2qOYly7Ymw1UFLNpHmw+t4TxS0ijEDp3EklQQqqImpMUKasKsXMSiVdz10GhdEo3aaIoQZKMo5siShndtGA4wmvUiYzHNd1dPFwKGG1uyWROSthBVong9q8zEzYtTkIIcaYQ4iEhxCNCiAs7vC+EEP/h3r9HCPG07e0rhJgvhLheCLHS/Zw3HWOdyJQvqcSGckuhS2YMkoDEdXULtU8jqOCYA/q7S/T1xMw/7KgscK1Ugue+99izUPZYfTcAcyLDwWvdyhhJZNKbrFCoJn0CGSGlcT7ABscF+YSppU8p9Ck56Nny64xELbSx4nxSFHKmZcK8rhJ7C0speWk/bxQl121PuZhL5IFJJI9oK3Lmy4iW1ER+O5LYvGWorRtY2oSlyP0nxkdRQhhN9yrbfbbetYS5ccBIv6ONSj2EvmLY+ZZ6LZ+shMsQS2tQhEkwsXUKcct2ukudRLxhA0YLtPts0mg8F1gf6d6b5rJctM3XAUk6KUqfShRktRHdjRCZToyJIpKGpGSd/jgnkabASg8jtEMSXpZRo10Kq23AFLDAfY6aEbT8URJ3rJLynb6QdbpzmkDgW94biAjo1rmTSGmh9WIfe120AlEGVyxYlSNc8PsL7LZxTMu1aI19bZ2EsG1XW36d/1e/gLmDD+NrSRpc1a4GABlkdFO5pbjOG0EJK9bXFYxwxAOX0CjbSd8TCVLY+1WNjpL4Feru88ZYJyF8Q61p78He1iKqxjgnkbC10Y9mkKjcSzmkLRAr57YvUIZKDyG0otrqI1AtpKgw0J3fe0YFaFlCmJjyGCehXeA78Wv0zQElIQm6smyletcS6sFS5sXdzB+x98Ttj87jscrJRD6Uh9YCnkUSRSdRKiF1RHfkqtSTStuzABD6dbRDEiNhE5OAIMlowNSSAt00dzRCtlqZjMqolIy2BjKZkwDrlB7yngqj7bTtdNlOOwkhhAd8CXg+cCjwKiHEoWM2ez5woPv3ZuDLk9j3QuAGY8yBwA3u7xkzFXiUYqi1QJRybRmwujrzK+vQgNLQPPQsuk0ZLSChxEgtobtrD5cC66HrfVmuf+zSVhcntgZhTqSpuqrcQHmMGHszRKWikwgoiQghDRiBEeVc5tlRVVr6SO1TcvUGLb9OPbIry6FmbKuVM0uYVyuxXGyh5fciRYokwHNVyunqdPNcIM6RxBNehUFPE/ntgevBrUNtRWRNhyQSL38wlAjQJkAYzaJVDwFQry2ht+Uz3GePF5bmMOgLhl3DpHqVnM93SMKTLniqFSaxnzcOE0yjkXX+i9dvcKjLyVsbhXSxnJGevRia15uNy9MBSpEFRANdQxg77p5GmMlX+EoRCUNSnY+nQDraJo1JaOGhPNv7QaROAp9KqgBMgkTiOSQx1wX/axrqQR3tZCsCZVsO5UjCIAOBcKnDEQE1Y0jSlqbOWbTqqTOro2Q1cxIVf4SWW6XoKKLu0FGSOQmJ8nyUSJDSIFWMb7yM+1deFYOlUDwV0qgKyi1NKCOMCOwq3QX665Wmu3siJBqlQY2Morwyo85JNBxVaYK0ME/T21ro6KYysUzoi4ZAD5P4NXpGHY3qFmqtRe3VxBt7HudZN1/I3MGVzEUgZIXRGkSpkzAWjYpSRDmM2/Y1SVofUmX1PIGSEPs1aqFFVI3qHkRuwbagbhWbN412sbV8OGFgYyQobZGESVAZkgjwVMQct2gLVLUtDgb2GcWU8DBs6X8IXwd4qHFIoiXylNpSEuE36xhdAiOoS0m9OYDnqOaU0vuufDGc/jFmwqYDSZwAPGKMecwYEwE/AM4es83ZwLeNtVuAuUKIpdvZ92zgUvf7pcCLp2GsE5oq+ZQTqIUgAoEpNL0XRiD8BlEARimaGLpNmcgHzwQgFX5QRQttUy2jRoYkolIPkiTrfdzd0gSuGnvRkE9Dp06iUM0sAwIR4gmdIYl0VZl47U4iiOtUw01s7VrL0odX8g93/ZDB0ZDFa/NVhSBh727NQjFMY8FhGZKQaGi5SnHjUa8KRqsCEkk/c2iaEnVRQklFPCa7aXhgpM1JKN+lFhZWT7HxUcZHGEWtuQWhY+pdS+kNJSPOSUSlOfQHXoYkGlWV62G5ybbsF5DEGuts13/hv7j1Z5dk57rlD1ejjcS4zyYKq7Mk6GarmGs/J4qn/8mnPOJlAXJf15DlxQDMG42QTrm0FGtiaUhO/kcXk0iRRB6TUJ6xzkYa9t0YYhJJzd/gzuW0klQJbQLmOumWGoLRoO6OlRCkSMKNuadppZlSgYbQlOjWhsgFSVMnEbrYhx+PEpe6SUWBSqJF2q7CRBGNNBXVNwjjFjKeDbYLYWMJZZ3rkBlp1YiVV8ZTEa1uzy56TIKRPsqvIJ2+01C3whchnoiRwqA1REOjICShW1iMOkrElEtIown0ICc9vJA5LZ05icFkFOH4/N6mdeilHvtdjs4tTlOajfPqBEkDAQRIEllDB9CsOOkcymivhCdDSq12JxElTnDRr9IqSbvQ82uUTAMvaRGVeondgm2u00RLtCD05xMGgoqxIp9pTEL5qVCizXjqcdc60OORRDNw8TRTQd76ETwdIFU9u6/SBV+Eh3Jinp4KCeIGAklJVWgIwWg4wIkPuZoW5ySOaS7hph+tZCZsOpzEnsCawt9r3WuT2WZb+y42xmwAcD/36HRyIcSbhRB3CCHu2LJlS6dNJmW6FFCOoSsE4cs2JAGSAU/QCoAkoZE0qCpJ7Ft1SyE1QVBzMQkPnUSUdFpsN4eKHEK77IRqwyBdaufiQY9Y28k1GkM3eSIhkInrd1zKcvMzJCF8pJMBf/otH2XVvNvY75FVnLH6Nob7BpgzkOf7IxOWCyf3/ZRjM5ThY9DZSsuj1e0Tl0C4KPIA3dRFkNUAFK010qAodJZaf9ei7HdlAoyRCKORRlNrbKZeW0p3i4xuiko9DFYqOd1UTfIeHS7oGPgpkkgIHrMxmXDrEA//5FvZuZING4nxMI7MHsfzDs5DqghpWiwYDVi8RuZS8H4N6VaN+20ICVyzoUApYqFJKr1tTiJFGlp4NETgkIRh+ZYYTwdUUqrEFQP6ugx49DiOvmwg9FtIbZGErwM0XuYU5jRByiSjnyICurQmccHM1DmretopsUFUypGSL0PcXEizOZIhCeUZp24srdy8UOCQRLfW1mm6GFfiV52TCEnm2Hu04oL7sV9DOB2u9XMMgWhZugmNMRAOumZEzkkYPWxrdQLJSAV6BjZQ0gtZtNEj0CVir8m3u1pUHJXYFdnPUt4vYcGhIwz3pIFrTUUOs3KZ5qoTBY/vJfCiUevQfEFUtpNyLC3N6HshfrNdzjxVKVZeBYxwdFMNTyaUomHC0hwih/67Q3tPKC0Jg7lEvqRiDGhLZwoSlJf25Sg5JJEQeS08XW2LzwG0Ck5isLURXwf4RBndlMqfCIIsJiF1lKUSl5MqdSkZDYd4/Q2eu7dyGrjaPaZuappsOpxEJ2WpsSpZE20zmX23acaYrxpjjjPGHLdo0aLt7zCB6VKZ7qatNjXlUlsnLWkkLSkJSyASRTNpUlUesW/5beEJ/KCLREb24UuirK4tDnqoiQHSeaPUyGmURUN+FjCNS3k1s5XlgJqMrDiYCDK6qZzKVEsfia3RwAj23QTSta2sb96KLKRLeUTsoezqliVHZU7Cw6DiVGzMQ/X4NLv2Z8OCs6lp6DfdtCZwEiWVjFPRBKgXaDOl/cxJAFTUIHGph66myZCEkQED1fkZ3TRYNRnPa1wGU1BJc/UVMmyC0SivzLL1Toiuq8rCYVc/4OimLGPEKDAxIqzZIKeObQHUaJ410yzXEJvt79UoohTYsZWihFgkJDrBVyZHElm1rcd97IMWHlIKKnEEBARJKryWIwmAssvB94wVCZTGxiQ8bZFEOkF3NUESkT4KkQnoTVqZk0izkESjbq8FIWEBiXoizpDE5qF1NNNiLY8sJmGrxHWGJISjaAKXYGHVfd3iZG53dm3Acvg07e/r54EnQjwRIYRGG2i5xkQlzyInX4Ucd+enqXX3M1yDWnMLzeoiaqO2DkT3PMDjATxnaJO7t6yTCHtK7HHkCHU3YS6r3sVTyr9HScn3nusxOEfiudRlgjKtUhqAtqtw34vwGu33bWZCUlJlYs9DeWWCwK7ko3IvsVuwlZVzEkgQHq3KIvrrJ1ohROOQhLuHYs8GrquRrZL2TAck4duxJqZCXzKKrwMCouy+Kresk5DGBq6Fji3yck6ipKrUpWA0GsnuXd/kTuIpJy5hJmw6nMRaYK/C38uB9ZPcZlv7bnKUFO7nZmbQTLlKzcV6W+W5+IVG9anwWRiAjBOaSZOKEsS+wNMBIgjwSzUSGaNEQBzHmZOISj1UxRCJy+H2mjJzEguHPQLVTiFArt1UE60MSaQTU1U6WQoZIIyfFZwdsMHguYd4ZMv6jBIBm3myR2I5V5YemdFNi2oecdrkRHjUew9hdMF72LTH6Twl9njU68JLPBbXI2JHlSQuIF5Sqo1uSq1ckJHQygcjsocgkA0Sv0K1qRnpa1FzjmHAVDMksbU7T4FNIkOzBN3OQQmdIGJti7bmzGfpVnstNi/0mT9incRYJOEnTcrRT9x3McdWBcsSpTgPkD+6tAu9wU7o9XKYOYlqrFDEJDrBc6tHyAPXWkr6RDdG+gRa29dlQNnx3sLRVr5bCPzErLaoCokSqZNIbMwCaXsVYBcqwlOuk4VFEnNUPA5J+MlaVwOT2Ik7/b6FIvEsLtkytJ6GC6ZKTyBMgi5VbZW1SBDS4KkIY8po4VNydTthaS5g6Q7m2997nTS48srQSlAlTb0qEDLEIyZRCdoIhocsip0jrcMJEuipryOpzmG0BtXmFpRfpdyyQnOxF3JwGLOs7pIo3Aq87ijMuou1HFf9Caf0fhWh7Oth4CMbTsvFr2ROIrXAD5EFWY6xVlJVEneuIIByNEy9tjiLiXlika32dtNk1PNC7u77R1pDVUAhiNudhI4oxZD4IRIXkyhIjxeRxBZp8LWLPWI4ZOgnLNto5WOkyak++z07Nd6kRkNI6nE9e0Y8hyQaKJKg05p75206nMTtwIFCiP2EECXgXODqMdtcDbzOZTmdBAw5Cmlb+14NnO9+Px+4ahrGOrHV8ocs6l2CL/NJO+113XJOohE3KCXWSfjaR5YqeL5FEsYrYbTK5C7C0hxqYjCLPYgkb/7SE+ZIomha+ggJXbJpg7GixGgl4neHCIylSTPeGA8Qhrl1g++CuGHfpuwGA5uhtCheD6UemLcvvsuQCnRClFZqCgnlHM14wEOlCnsMefQOaF5933x7bRyFsCDIH56ilSk6iRLCSJRQNMogynUSr0ow4qMSzUK7UCNRVRrVxdx63AfZ3N2TxQpaEQzVYK5OYxIKGWt81ULPmZ8lB4wuEfZ3HYBpj0n4SQuv+1fcu9dPOejhH+CrEJVx7/Y7fnxJjfRy3XlAjO/opkqcoAiJTdxWTGfRm6uudwJ/gdJZQDst7sI56krsqnH/MEzJsxNhImOkdkjCBBjjtU0o0jNZ4DomoFsbjGh3ElXVRBhFy2sH34HxOf/OT7Bp0ZH0j2ymEbr4h5QIHaFqXaBt8ScydXolixxcYkBYtqt5T4ewyN50C1s5hSdVjOlxdTIyxBMJUWKdRL8rtlvkJCrSdHFVmUejBpWWfd8kNi059kKWJ3FGL6bfz6hLHW26BIRSioDdMxOWArymHa/xK1kqa2olP8yoXQq0THpvlJMqkXMS5YpFEnGKyIwCuSCjfQBM6Qj7U0ublCDijG5SoowwIeUYYj9EUCHxawSOQoP2mMQm36NkSnhu0XV460p6hx6z19aUXNJAhBJk8ib7bqoyKgXR8HAWPyqrAQ56+Af8pDxAY4YK6nbaSRhjEuAdwLXAg8APjTH3CyHeKoR4q9vsF8BjwCPA14C/29a+bp+LgRVCiJXACvf3zFk1dxJm/v4EXs7vpVpCYSCQsaWbSgqavo+nA4JSgAgqKGlXqRhDQGCLtUpzKNFHo+AM0tW/r3xKajyPmCKJbtnCaEs3KS/mCy/26JmTtzA10kdIgfQN5Rh8l5+fDG7JAt0AAREHjtwK8/YBv4xMRfLimCgtfgNKxdoQAz+VT2VO00OahAMft1RA5CiEJVUPOiCJokVxBYwkkZp/eLPH6MJRC8Hr1mEunJv2U+ihf95TqHfvyea5S7IVfhQZhmsw17RsE0qTIAx4SYiq5bRWa2EapfXziTxFEqpFqaS4a+GvWL7+twRxhPYCq63kxr9hYQ2ecRKGhB8+C3z34NZihTKhpZt0PrkIo2wAWEq0tMkKpURnCAOXQipcTEK4yf3/3e5x8ICNqRTpJml8DDktB1i9HpcG2Uudbq1tmiu5c6tGHtIoGmO6/FWTbipJF43aIuJmnZEhVwshPYyISKpdCC1QQiGEsVW/pFIcDkmU59p9VIhcasOE8wv6Yp6KUK5hVKn2B/Yp3wUoiySG7TEWuoB15iSqc6h3g9CO0nLS89ZJJERhLlAIMOIm8FZaTOrou4oTy2uWyvhpQaBXy7S5Uqv4rRz1mZx2KjlxyVKSxw2qfpi9DtBVX0cSLMi+AwAh8mc19hRCxjk1KkoYYkoRKD8EUSX2q5lDhNxJtHSNP5bL+LpEOs3IwGToXxJYh61D+ntAu4Zmr/hdmVK/R7A1RxKohOXrf8uoB/VoYtS0MzYtdRLGmF8YYw4yxjzFGPNx99pXjDFfcb8bY8zb3ftHGGPu2Na+7vU+Y8xpxpgD3c/+8WeePhNdOadbWn7YGLrJNZ0JDF5k6aZSbIh8D88ElEtlCKpoGaGlbTXp49nVmJCMlkaQJi98kiZtj+pnq8zsXKqJ8gLwfTypbaBNBtmEs4eD1LFnnZD0BNqXVsk0sTe5GOrLJyysmuiCcC3M29f+7TuhMmX7YOMorMDLK1sXhCM858FVSOMhpGLhGqtUGbm0xkVl2TEmUbRIV5yOv2awWzBcCtFeCd10HfVc9kpgeqjFduUqRDV7AHRTMVITzNUahckqsD0dkbjrEPrQ6Eodg4/Meie7IHPSosfTRE5/xFex/Y4K9F5J1ZBPOZjIizhi7mEFJKFInJMoBq6FsamkWnpoYVFdkMTZQ55y0VK3B00T6fO0LVasUcnYUlg6QRAgTLuTkJ7JJr2Vei+6tM5SXNOxd7U8hFYMlNrvoVLisnz8Emq0n9b9lm7z/YAnFsaEeyzKkISQtKFOjF2Zj3Rb5OipCG8/W709byD/PFJHhF12YaUX/Yzju3+IEAqNpFm3k9o8pyVWcr015vbU+P2Jku+tsM9CrKyjj72QPRNFkngu3mRnzkFXY5Q5CUeTznGpyK1yJaNijN+Flu2B4u45DRasOBaAoVLeaKdWddX1qpoVvFW9epZdBDB3yEqrNKod82W4e39FMi/MFjSGMokM8ZuCxAsx0iKJWjOftobL9hl6TC5kq+8htY/xXT+Qks4Qahq49lTEULegUbbXMwlqyLqg0tfMa4lcpqQSHo3d2Un8JZjXMzf7fcny/fALSCJV8vQ9g++QRBAbIt+3HdgqFfAraBliZIAxAl97hGVb/3djd4iv2ikBKazuS1GLH6OR2rYxVXOWgQAlUk2YmD0SzaEue0iVyjYLKvDYIBdQSQSe6/bmjwy1PfgpbcFcW3wVdNlJphRWMEZi0qB0kK+a/t+qW3nNLattb+y5Gj9JMCYh8u1DuaAkO8YkiqZ0GZAI54QGglR3yT6wPWUbtAt0T5bR4psqSvoYo5AtSzfNU5pEFOmeFmFKSVQEjXJaQOfhkUtQAPiqyRyZOElvm02kZV7VDZbr1bFhXncvL53/sgxJlENNYkKUVo5uSntEqDyVVNqfQRRnWU+J61tRjAsBrFoScMQWG3KTIsroJoGPRGYxD7CFZyl98mPzXK5cdtE4J+E55NRXau+oV01c35GghI4iGq5ITvoBjXKESiTCCJQ0vDd5cxvqNE6jrFGz966nQkpLl1IvQ9dQvhr3dEyjq5uK1jwSpFpPGoMgdi1cu1weeMmtVxbO7ULNKfHHPe19Gkn7ncfSIgkS22I1RRIDvv0cLUc7pUhinlsstMpVPJdaLrwaiIqVrnFW8SL2eOUZgE1OSBMB5rpS6rKqopz0eE0MUy44iW7X1yOsdK7hbZQVyo/QXhdaSAQBkRcjmxLlh2ivB+2V2ho2DVf6MGgeFkusHL6Rtq0wFkkIbPywShdKlpEqYrBLMFCxCQqxX4VIUu2LCmnijqITkvruSjf9pVjQuzD7ffmeS9tW1dJ4CGMIPIMfKWIdU6pHNCsVBJJapQpBFSPtDa4Bz0haDrKv8wbH0UqeVDYTSo6loSyENfP3RkiDcTeDbyJ+tWYd+82xGQyiVMVIHz/waHhlyrGHUnZVUmoM5ROU0YwKB8MdkqjuYc+5eMD1p3D6L7onz44IjOGnx5XZOreLdOglhhgp25VRTRiU185zpG7Qcxx5osp2hSwU0hg2lVxvZNcmtCwigmiEQM+hK7LXqqSqJL4PJJQaMFyDeVoRZ9cHhGrRcierV2E4iG2vYQJKsr1vsJ+0mOspbBqP5dKVDNpE48pJDRUZgrKPX6plKbDlJEcSvs4pLGEU0iEJ5dnYhB9GWUZZiiSCpB1JrFxeYq9RS8XM062MbsqRRIHz90wm6dJVDkhYRqrhlTpnm6VkGDVz285Ti+zkqr0SWhkaaTaUXyLxIlKGRgvNGrFHWyZcErSQKqJVzp3Ewnl7smlunpUHNsNrsNbNinqTX3R3cUXPHBpB03YqdIfzXCA1pZv2mNdFxSsTusVCeo7Ya7E8TiC2jjWdAH+12KZth46+S7PyFrkFUKvcldFN0utCiCrlMKeMfBHhpa06AwFOfbkrfMSNq5oF/Guivw1JDFasjHvDaX55SRNNRMn1AFFCQc9dIHvYsvBoJGUiP0Q0JdproRxCqRRavyYyJCrX2WQWcUTL3p/D7ruRTsfHNxFz5FwS36YfD3VJhv5/e28eb9tR1nl/n6paw57OdOf53iT3Zp4HIJEEQoISkIASBhXhBaUVeJ36VUF9bbVfu8FuW7FFkFds0raKtrwKTWMjINKtLWJEQECRMCYkZLzzOWfvNdT7R9Vae+199j7zuffcZP0+n/M5e6+9hqq1atVTv2dsCyadJTVNVE9oP96rqJt8tmlVM4kNR9zp+5nv3LOdwPQnEbHCRO4eZODD/MPZhPnYDbBOo1kyiVwC8lxQuSqZRCrHCLOKS22r5VRJypTU2l0nwVq30mXLQUT6KYg1XQSLbk+5faM2VjQ6NHRNQJj080k1Zk+UTEJsyvEiwdi0YxLN3W4S2e7Temc+aV46sRdIkdxNgJ+4KEUkdHWcQ7i+dzf37P1Td0wvIQ0rCQb1PImPkC269A0O4DJf5WzPMr4RuTbN2TY6UOi8R9g7QZROlkwiTBskxnlt6RxONIWtueKkgiApCvl0SXzcyckGHAvSctIPfBuKCV1n82zxaopMW79SHWISWYOsZzGhxoQxRrqITYkScULCtyWaP4rkzp9erLNF3L9FY5UmPHm6TJlSColkiEnsCMrqg5N0Ubn4TKIu1YUaUjc97qv8tSODSfcSeHVKISSc4VxxurKgySQpKwjmyiC5MOd16RKEJKpHoQWzypKJHmASSWhdBLfuC4kD2w5z5LKnlx524FR+DzfavOTkSWaV4me3TjFreo7lpCB5QtB0Y7dIqz/dadAwDRJfxbFYpSe6x640Rbop2johPh/AP888RFc0vSF10y7v9jnfaGOKzMe6jaJB1DtWttFIDxX7GiKhLhMkNsUJgChtkHmW0rLfLIVEV8/y4DZ33uNtt5A67yvv51j8uyhvjM9VxlznU9jsIb564NsQFPNBQj6vyCvJME1yynnjkZGrnLnoOL1shmtm3Th9UGIQi3SM8zSzPXKMExJ5j+NtxbEWBOkcqWmS9RRbj9k+k0gKdZPiVM0kNhYNX6QlFzDtFmFFDaSsppMrtHYGYrEWfXqerjd2T7Y6YGKs9EAUuQRIBrPxDDqd47zJXZi0MgF0OmgfqVtlEi74KiVXAf/62P/k0UCVg8H4QCzdmgIgCz0FjwzzOiRIemU+qc78qdImofKU+2QHj7UugN1XAxD6YjfTp73uvMj7P3U+iEsTkIvha9tdRHkmoNuW6PHHy3iJrJeRhH0mMa/nypSCQeRdBomdcVhZdqcpp4Ou33eSRjvA9hJasw8x1dtd2iTCLCbVply1po0cYxq8p9Vl39e945udJ0uFTOBUAx6KbD/Fhh20SZh0nm0+ADEzbuWe63BASIRpkyzJCUKNCmIujD/K5Y/+HmECiZ13NokMJk9+lZv/8seJu8ecIBXN17YJqdKuNGbH12vwqUmKRH/lPYqC8nl27Dwqd8khkQA1xCTEWI57Z4dOaOilOZEuxqgmazvX21SE2UoZ18ScRnkjdG407Tk4VkTvBhGp6lGk3LXKkik1MPknoXXeNF4gie0hQcDkoSMDTMI0ezwaT3JFt8flSYa2LleVVRpshLJdmsnj/v66Y3QYEE+fDwKJniuzDPT0vGNqvQRtFLl2QsKK5R9f8jv0ikqFfoTt9jUsuo1JZ3S3GVacJqDKJDQ9dOSYxKGdbXzNIMIDV5KqjCCLyU0Tnc4T24eRbfNYcuaCUzywz7neHe24d7x96n5efeVN5N4VPJeUk1roZh/mdNsZ9ufCHuSCzh3bmDz+BbY+9ll0Ok/uWdDR4DFa3Wl2+iy3X422cuF3fpPuwQtLIWElIFMRnZmT/PmVER+8VjHXnKUXNFFdYevxfiyRylLQGkRqJrHRaPlyj7ORQkQwVXUTmqk8RBuLyWFn1oY8J4ndKmOi0YQghiLQjQjJLHPxDHH3GD94yfdjsqT0+9adNtoIBMFCJuHVTY/kp3jE6DJlcOEqp6ecIa3wJTdRQFeHREn/ZZyY75ZMQuUpj6kp3nfjH0HbHatnnadSZ75Qi3hbAQ3QgrIpJ+MG85GgrMvvGTQz5PG5Ml1JniQkgZuMdlzc4vOBlEwiiIqcSK7amRXL7jQrPaPmgwmiVoBNerROP0CzN0XTr37DrEGmDdr7t6sox5om84qynKnYLqSKr+yE+7fAA7GUpSDNkOFaZV0igU6W0zWCygt1k/dY07NuRdnLCSKFCWO2BPdx/uxHnc973iXJkzKrb7HqLoLSRKekRqPyjIcnPfX3z7kIPiuQqb6QaNBFF0ICCLJogeH6WOYm92ao6SY52qedt6JQ01uwokmUIg/6wjqtJGLMQ83Oo5YTeFtTY3qggJNVOekQk8gilwuqgHgBG+zbP+AMEV3R5ZRqIsDbT2veNh+TKSc4lY2RvMupS17snmkxdxnD/d7LSDf6U0+qumSJU02Z0Klgiyq4X5TZQqNCD+GUjZn0qsS80UJwzgkWx0qqHkpGElTUoNEJuOLI1qI6K8cveB5dSYmymEw1MNkcau4hLvvONrPBSeaDUzy0+1Z3TR/kqvMe7ZmZspRuJhlHVcBp+TihF0xJVORb+mue8olf4LyvvxOTddHZPKlnmSfDo7R7U8z4ehn3soPj3/UnnDxwG+KZbiaGXIc026c53tY8sEXImqfoRS1a8zA1C1nLFxRLvZCA2iax0WhNOCEx7ye4yIQDv3/37PllfeVr1SEA2k3nN91oGDAN8InoMj3Jo5NPZ76xlah7lBnx2Ui9R45qd9ATW7Ht6VIIAFgvJHpBhyPHXsUn1ZWlYVvRcy/gXscGCs+XIA6ZN05IlExiLuu70+UpidIEldWmvusd7lgfIxH5xIBJN0O0c/U83nQJxbRVJAhxqwfHeuQ+WC1LMtLADfQbbruAexqNPpOIvWE8TbGiyBXsSlO63uiNKOKGxiZJaSAsEKUNZuOAoMjbFGbYwEfSem8qa7uoLOD/frnhD29WdLVmNvbqJjtYYAdSHjK72JZlzPq07lV102xwkjhtkXp1ky6ekbGYFJJ8vvRuqkJshlUKxOmHxWY8OuGD33xah8b8YOZcq0wZAxBJ6gztfnVu8nCBC+zjaZGwTzOfZmXhGSsaNT1NrjTzolChKp+11X07iDWGrSdA9/xxjSaltAMomUQlv1GQl1HXAKowPu/bWxrmAXKxnPJJESdMiwtMm0zlIApFg561JNe+2p3SCwkxhlv3u8l3+/RWfx8Tnn96O7lvo4ncPZoPgTzikw9/sgxmPUnMaeLSu8l6Jm+yeWzmvLGiig3ASBcJGnzXzz2VK2/dy2Tb3c83fegLdMUzCR1j0nnEdtGPfoGjzW9yNH6YZvMyfwPc4kVlCaozhc/GTq5SjqqQXgCXf9a9TycnHYPYemye1uxD9DpF+7pkKqGZ55wKjxLkEXHio7kFpi6+hbg14TzN8i6ZdTFQRrok4t6ZWE6RmiYzJ11+OTsx5e5fkqGMQYSaSWw04rb32fZ61Kq6yW2/gp6f0C/NnIFXN93KPIo06ADjq0TNt5/CQzuew3xzF9H8UfLT7qUr/L5Vp40ODDZyZQ2LpHSQYCVhtrWL7XNXczK4tZxUFF1OTV2MxBPoQJUeNGEzoqcDovlG6UXS7PnoYJuh8oREGQLdd1fV+wcFTdOveAshoWzKyabG2Bkkhx6KqJlAkjN9smASackkRAmhVqT+EmHDtTlOMl+QB/b4nDYFosgln2udGhQSYRbzeNuU7q7NKANvXBSf+dIWq1Ebl4KjFBKeSSjvUWXJ+N7417g3OcIJE6CzpB+ICJyOjqGtYfZ4r7RJgJukw8TSq6ibqnA2CYOoHqDpXriXzx1wK/bCFtWcPTl0UFCqF0Od9dVNgEJRLVOrjOVRX1kw1EI3ycsVtRWNnp7GimZWNMo/B02KqEpDjUJZmD7tVZaRBlPxstN2AZOwgZTBWwDKG5+DffsGmMTWqZBTvtgPYYstwUSZpj3XTTKbE8e+r/4wMYZXXfYqPvnyT9Js+dQZ2TwvnA2Z7bl9TSN09VSau+nIAT7+4MddWmzpMac7zEmjZBJSCIl0jtmuU1e2T32j3z3pQdAgbgVordg66Z7tc6/ezbaZiDBtYFUDnc4hYiFPuOCaj3HLy47Q8vOA0GcS0ppEPAPKJOO4NvSMU0O+9/APc3ynz492zF2/N+GPTR2T6ORwOnQ/2mS/f85Oc9FsTyLKomziPCRVSCDzLr8W0JbTZKbJnsc8U/ZCQmcpGEMrNDWT2GhEPjhLOm4gBWbQG+kLO1/IH8szAdhzeju5GFpT3m0zdDrBpiqK0fSDeuLuMXKfDO1kYUdod9BGYcOITIXYoFBTJeVKHVy95bysndvjxPbr3PFGkfogn6AR0pho0+omCx6mynueSZgBJqFMUXjFtafZ65cElUhzOsp5aAYiuwOxrrZy4GMR/tXvZy7aOMnpBe48ooTAKFI/QQdeSIQ9V4QpF8Xu1AkJ611UoyDHJgkNe6pkHrO6S5g2ONkMykjZTpCBv2956dXj7leQRVz/9Tv49s+9ntMNbyQt3FQjr2JRlgdOWbJ0kiToM6zCuHwsdtleuqdTgkhjSiaRYzJI03mnbhp6/4LkNKlpgyROJXflBQTp89y5oikknxuYfN3zCEhDX5ZSWXSuBvT8VSbxVv1ivpC7tBWRUXQTF83s+q8It8yQi2ZeG5S3AWnJSvWQu6C7r6WQCAMIqkwCMqUHJn9i3Vc35V1U0zPWXbtcZTqP6XbEf3zl092XsImK2hg/oSVBixRL7J+JOeV09uKdQQIVEDV9Wom0x5Q9xumkYMYBuQm5YN/53HnJDTw69yhNaWJI0c1psqDNztQFVcbNraCUVzcJQkbn1P1lG40kYPrxEcYzrudds4dGyxBmMbluEKRzyHmuL6+Ot3LXJS+i3QzIyFBeSKg8QTWbaD8/5JJxQilONMEKzDYs+bRbaE4ed88p9UIi6h1nNjxFJxdORccAmE/cPVE+TqLVnvTqpp5L+45L1FhgkpNkqsGWon5Te9plok1zxBhaUe3dtOEImt4dtOWNjkNM4s6rdvOcK59CYpp8/h+fwhcv+A6eeqlLO2X8ZNnyNolc+5QG3WNMnvhSySROebWJ6nTQgWCDyAV2RUX9gaQ0cAFs32L7Ngm6zO1wgUHaSJnHxzQitm2bJMoXDhCdeSGhDaYqJJQg0p8o4/m+ukkZ4VScYjU02e2EBJqg5c6/85jzHMrTjMT3WykItJAUTKLpVSqJm9BSpdidZiCWvMj9pDNsr4cKArbs9vd+MiXMGqBCumHObAhbJUNFbsWYFULCx4MEecTW03vZc+IwJyedeqDBUVCqFIRWWU51U2za8UJi0AOpuaWvzzehIvIuk8q78d72KUv+zYcXvChR7xhJMOmztSqUEXo+HXlmYshPD6TZADDWkPiYgjhw8TfVCbrqgvmN+FDpUhwqRVapZ22VZurOO3msMU0iyo8/S9iKS/WQ64Pr26SvZ60jg1TXPsqSiRqIqUmmQ75YMKKgi/qR1wBugt//f93V70ukaBexRWEbwjYhRZbYFseCiCjyi4XSJ7biUdYohMQ8k/OPM+cDAE0ckJsY1Wxy/c7riXXM03fdgpGE/Xt2cd6enexNM77vawc42Loa1eq7wU7qBwljC34hop/5E+UCA/rvqQkUYaydkPCxFfLMn3Q7ne/UYe3I0FM52mckUHmCimOi6SaKhNngJKeV8PGLhP/5s3dwvCXoqUms9IVEPukWnvu/+l/50JF30baaU55JnEi9NqJggXHbq5sSet72FEifeU9xysfleK+mVsctMDKLaE0rNJzq1kJiQ6GabjCEk1MAbKukvAY4tKXFc66/iBMTBwE41dqD8i6w2g++jl9J5WYSyXp07n0XM0e/QH7aJ1ib9MKj03ZMImqSm4jcp0xKdEIm/QcdR/1BoaRHb1chJBRpEWTXitm1fXTAj84SlHVMIqyomwCUlr6r5ny/brQ2LteSspoJLgCgiy6ZBLhEe1ma0SvUTSIEFXVTELqU00HiUnfoIGRXWqgi3AQfSoJNEiQM2bqvTRBptu0KiNKYkJBjWw1ve65ie5ah/IueFcO1ZBIxkZ9cTk3dikpP0bLHkDBEFf316pI87ZAYykn5c/td319z8yvLfgWhJgwiUqsQr5b5/g/mXPJf/mbBvY26x0mDCbTPOmuMZsvWynOwpweYAbhiR4lnqE0tnkn0hcTU8Xv7+zYbFLkSI6PIkn5VvFwUk0+5nmONSTKBODSEjYBwy+TAah8xJBra866yoYlCbEWIiHb+9dWgv0ZgeGCyiGbvseWmZ5e/da69uF/6NtROOACELQhbRH7sJkGLo802yjOHQz7VtwQVjzK/kNBZl+bx47TTNihFMNHENju0nvoUbt1/K3/1sr9iS7TVsaTGNBK51bpNthIHxrmT+/bPmPs49DMvJogMOlDIM3588P778WpC7e5XFmO94Vq27IefPQqXfYfra2xKRwzXzgSJY1rbZnj5th/g/unPcEK7olNcchiAVtTGRsKEFxL4QleZnGY2PEHLambDE1hyTqVufikEF2HbqZvyHokqhESfSWQtp9ou2H8et1yMTWohMLzpO6/g9bdewEagFhIeEoagFBfsuQKAdiV1N4DNLWbnTk50nC6xc+p+cq+aKB70hCqyZE5hsjm6no0U6qY7v+UiwBuujYJGCzs5g3Tc4L1va1r62gMk2DJO4tP2AGrKMRdtFKlPehY0Y/bunhnZJ12qmwYN1+4cUg64wtc89UIiV05IzIgbdPMYdGiRMCcXr4+f65L4ibiwSSR+7WuMQqwrpgMQRDEhMJ1CHviUCHaevOfcK69/7iGe/8NXETY1YdYgsAFpU/M3Fym2pxkStlDSz1nUFxIhsQ/My/UErVNfIsrFCQmf6l35Z2PTjisS5Sflj1/ijpvZMlmqu0ykCY2iR1AyCYDZcGH2+qh7HKuj8vpaa97+fbeUv1t7ekGBe533mUQjUGg7qG7qnPx6+TloNCpMQsh7RXDgXOmZZXyMcyPQhLF26rKKzcHagEcmhda8SzWvwnDAcK2Mj5OoGK4bkeGUj9BOVZep5lSlA2EZjR6EBvyETdCEsEVcuC6IIjOqVC9pHy8ildijUt2UdUlOZMzfnxJffhlBM8a2J5l+2ctc33VIlubo1gRc//1lEsqjtkNkFKrVIvDXnTH3Ee7fg4lMf/KtoGQSoSJuBIRZAys+tYcJHCX2aEeGXiEkbI7YFBXHtGd20daPo4DUT+IzsXv/WkGLLDY0Zn2qjWl377peKdEiwEpOZo4zn0z5tvgxHbacuqnyLEyFSXz1Qnc/kqBJDuRBA511kcwi2nDDoRku2tlPLbSeqIWEh4gw83+8kolvdWH8wxkn8twS7NnDiQnn2aRs2o9h8CuUKR+4k5s2Jp0rV42Fukl7G4byTCJLLWmSE8SKVHokJsFWDI+pzfspCqRB5FUoOlCkvuatbjVoTwwKtALx/GNE84+TqEF1E4A2FTVL5vPfWDfB55Khc01bOQ+MOT9pbL3lce5+lirzFvVMX0hUmYQ2GrEpxqchF++rvjs1EPo8Udk8eCbRnAjZed4kQawI8giTRaWudluWIWGTOND9sqZ+omqlzZJJAEwdu9el2a4wCfEG7UJIFJ48oU83rY1iYotnVKETEl0CpCIkurLQIBj6oK1O100QJtCI0eVKO2cUkzD0jMtU2wwiLyT6k0JVqIStipAwmjwdISTEVc+IA0UQG4JQU5mHyWzI0RlDnDohoeMQgkrtduNUeGLTUjUWB4bZYrWqekSVcYIO+7VIQtPPGhy2YdeVdFQ/rYs1iqIxuXeMkEqEfqFuMlmX7tGAuW/M0rrxRkyoyIbqUmeJRTcnYO+1EDkVzuN2gjjQTkj4d2bG3AdhiyBUJbsfuP+luknTaIZuDIhx3k0VlgPQiYNy0aPzBAGk0WBix35e1vtpurbf12kfFNgKWjzU6Gsg9IzbPu9VfE3vimyDY+BjWfpMooVSDMSsBNLlRx8/ysRDN9Le5fr90PbrmW8Iaa5c8kVvk9hI1EKigh0//uO0brgBcEKjCptbJAg4MemSnRE1yPyLWwy+6Zv+Rbm/TmfJvJGyYBLB/v00n/pUmtdeSxBrurMJeWoJI82J+DFOhcfIm/0HnlpbxlEkYokK/aVRJN4tMGg1S+PiMC773Du56J/fvcC7qdpmbD6YVjzQrvax1UR+ZXWUFpkKaW5N+PJOQfkYgV4xEQuERpUusFqLT7XshUTDTTrff2yGg9td1HeYniqZRIGg4RPXnZ5COikK2JI576Y40OUkY3xWzIlswqXUKOpjPHYvQWpRYch29U323v8XmMgbewsh4SflMG34eyl0tjiBYULlmcTgS6fmBgvXSByXQVulkDBF2xYREjYg0QaxCbFpEGSdcsKf6RRGX3fPw3ZzgEkYr3vS6XwZca0RcoE40FzxzL1cdOOuASGR2oCj2yJyn3baBGGpRiueU6qUizXwYyA0QZkB1qre4HugA1/LOkVHkTMKT+yBmUNw+YsIb39JuetsU5XPy84XucH6z7pgEsbOc+wrDbDQvvFGTKBJk8H7lmd5aWMqVFyPUTCJZikkpoNvwNQBx6iWYBKNZsWgnc4tmGinmgE93/Vi4lZRxI6JmL/OL8X6RVqsY5peqLaCFv/rvFuYCzRdA+EuVxK3WwgJn8X38UoG4zAqmEQb0bZMWAgQyiyvOn6Sbzz+fLbsbrNr5yz37X0mJycnSVLHwiS3SFWQbwBqITEGo5jE8YfnyqyRNm6Q+cGs/QCe2bK33D9I5rB+BV0yiU6HA+/6T8QXXUR7OmbupJ+wopA/vuxX+Lu9H+TU/n56kMRacuUKDmWi+0zCqLKWQ9BpInF/wOfVdzrv2ySG1U3FS6dtOhDpawJNrjJaapoXXLkbgBPEfO7WuwmsS93tktspkgEmIaRFSgyvbipUZeJrdbRo0Z5yL4jpnSxtEgVCLyQExc79Uzwt3ObWW0GD2KhShRTiDLxbkt0oFP+w62PsmP48kyfvIzztzjkRzHPk3v+KKjKVeptEob++dvqG8l5OeCERRO4ed23AxL55/viWCzneBD035KXUaRP1xgkJHykupxkuoWpyQ6ICJE9omAbaGqJZ5111xV6fKsIbg6NWX0gYJUT+S5CeBlHY3KJtwSQ0l928h8PX7SA0/eecEfDweVNkyjOJKBzwbtJGyAp2VtS+CAKShothsBUnCneAUzcZ6bq4IBH4oU/BdS4e4sIdF5e7znV0qb6xXV8PpDIRh55JRMEs6axBRYbGlVdiQkWeWfK8L8yyNC/fsSqTaEWa6Lzz2TadsefIFNM/8WHYd72LdwkWTpzFwigINa1WRUhkcwOLFYCZVkiP4t4koECCgINbWhze3qaIzGsYl2oEnJD4xOXP4HtefjOvfZ1marcTEvOhe08aPoo9i/ttC6rqJmU58MhHufzRD3BV8Gmyy57Gnd1fAJyN5LJrNLkOeWzrtaSpdQWhwKnKNhC1kBiDUUzi+CN9KU8YlyuewrVua6dvGwjSWax3wyyERHVC7Mz06WojCkhM103OrX5GT8ckXMWrVFWERKUClek0UY2+yuV0c2ERo0QvFBLFS6ey3sBk1o7aHNlymAsmDnLZLqfjzAXS/U9D/9QDHGu5YLsqk1Be3VR4N2mtsJKVnlnG579JdIPIGyyD+ZPYISZRTBwAz7n+Vt6+te9iecXeKaKwCJg7SioJW3tOKD/efJDLjrgaYlOz3ibhWZxu+XuTN0iDvrvnTuMEoNKqwiQ0RgldQkTBP+3ZRTeAYH7Qa0S32mXQViEkilxfprBLqdNOf+dhydF5QKrdhN0MmmibY7NZbv2L17HDu0Zqf6/iTnPAu6ntpX9RnyDP3TKhEBLlPfSTjsWS2ZBjF+7wtQl66CgY8G4yobiAQPpMIgoiml59maohW4xXNzkhERUnKYVBWHmWqmncO1QIBqUGSgLHLbfv9J5jHLjtEfa/8cVIGJYTeVpROTkh4QdX093vH33BTTzzou3s+Jmf5qq3/Twv+LFr0BNOuI1nEp6Jh4pGs//+jWISM62QxBfQ0nmC8nnKtBJ+7vmXUkTVTUaTxN7NthW0iAJNqgJONoWw5QRawSTOZxuvuuxVNNs7yutE3n2ZoIEoVxNm98l/4GD8IEdv/nk+bZ1dcCI27D6422WKDlukCaWQEL2JmYSIzIjIh0Tki/7/SDcbEfk2EfmCiNwrIm+obP93IvJPIvIZEfljEedDKCIHRWRORD7l/96+lnauBuKziRaTaZ7ZgYFrw7j0OCkG9pbWTKnbDdLZUhdfComgKiT6K5mG9yfHCu0jlk/s+++AExK5cgFgN5y/nU7sRtvE1r56ycQhqtE/12yjiE7u92WkuqnIY591y2I6ri/C9vZ2bC5kvg5ABrRCgwpbdGPlzKWi6RZ2ZBFCo8oID2WE462ch6d9LIdPIZCaJp2ZmCCdRZ0+toBJFALESs7MzlZ/IgpavP3l17LF+6gbsZwOj9M45Wwm8+Y00YQbevnjjyNhWJ63YBKh0YSNVmmknz+dlPehapMQERI/k2Z5g0RDOBSkpDodp6fO5hYwCe29h3p6kEn09Dw6N+Q6QOcJsWmirKXn1Ym5V2npiQkXc9Npl6zQaKHtH2iRejrPLcq6yOe4MiEe8Cm+kXkyGxBs206mQlSW0G41UBV1UxwqPvAjz3B9yhNyMqIgZrIVk0jCCemrRVzjAs8kXJDaMAo70DGV0yg83/Tg/wLFgiBUczS3JjQuu8T11R/31c88ymc+ep97DontM4nLXwwv/xOe/ZQriYx7XsMLumufc5Abvv3QgvbtvXCaw9fvQGtV2kTAqfAYEhLTzbBc9Kish1QSgN50wVbuOvAvefn5P85bbn0LHV/XfSKc4OR8QmFvCLz3Y2GTCE2HH732RwnaPrEmzjPN3SBBAkOeC6QZojXtuN+miTggnNmCzrrooEGS9NXEm90m8QbgI9baw8BH/PcBiIgG3go8B7gEeJmIXOJ//hBwmbX2CuCfgTdWDv2StfYq//cDnGEU465gCTYfXN0QRKSJKySvvECJTARFXeN0ztF7Y0qbxACT2FIpgtIsUm9EbNk2wSf3fAiABNwLnvc4sqfPUnae1x+wOlBIo//CzvtJsVtRQY32buoziarBVBuFNuIof+ajq7E0/QpVK+PjHRS9wiNV4Q3XtjxHajKOt1y/Ih+DkukmV966j5u++Z/JT53C9pIBJhH7ILx08rQTvEVeq8LX3a9EA5UzGx7HnPJ9NbPE0z7NwWOPI1FU3uvAr8xboebo4W388y63+po72SvbuueiaS65aRc7Dvmoey8kUhuRGGgMZvxGtb1HU3Ka1qmD7pl03OrQeIN3ogZtEj0975IlKueO2mjvQtmcno8dKPT2U3fdxZ63/CqtyXbJJAIROrlgov7qMc8sYhcyiQl/r406TUbIsw48m9Q4JjHZioqSFK4fWrhwp5vgXBBXSmQaTDYD/roxz4ONvvrUHVAREiZiGHOnnOB9SNsFQoIhdU7BJMIiY2rDCbfiffvMR+/nk//ja76vVXVTG85/5oJrV7H3wmkOXr51wfZ9l8zw7Fdf6q5bERKG3gJBExrlPAPwMRJRPPD7zz372/mJb/lezps8j32dffzKM36F2w7cxpcfOQ3eXhgFMVkYlN5N2teuMG0/vsQOPDsJDDYDm2VgNO2o38ZOHGCmpzHZPFkYuTQypbppEzMJ4E7gbv/5buAFI/a5AbjXWvtla20PeLc/Dmvtn/kSpgAfB/aOOP6soBg0BUvIc1uql3Q6hzUhWZK7SboywMSbb4N0liAwyICQ6L8o7emYohx02zMBTYPnnfc8fuWZ/wErlszmXlWQoCov2a7zK0LCKFRFSPT8pNhr9lVQI20SuqDSg+ombRRKK/I0L5nErZfsYPdUEQVqyCTFKs2c9/opbBKluskIucoxPotps9ngj7Ob+Nrk9ehA0WyKExJDTKJQAeRbvFqvKB0ZDAkJzyTE38B5c5p40glR2+0iYVAREr5eQGg4ecV5/Pvv8LUI/ISmjFtVPvPlF5cTR+FenGRNegbiwiRRjIm2z+eTnGLCe3AV3mKFC6o184NCwsxj8gCrAkyWEk8f8kLCM4muExJm2zYmnv1sOpVVZODVTTqW8px5ljsmgcvtVMD4JHOxLx50y97bmJ3YhsoTwi0zXhXoo9JNf9yqzMXoRKbJVCPgb0LDyc7gxIgOaajjNNQxZ5MYwta9bux9MkpphIPCYXi125wIuf3lhzjS+F9uQyEk/Pt28vH58n0bsEmsE8LK/W2ft2/kPrpYGOXJAFsfhdsO3Ebkx6v1QiLUId3D5/HV7d52Z3wEti9BnDL47CQw2FywWYooXY4Bo4Q4cO6+qpGQtxskvbysfCib3Caxw1r7IID/P6rW3x7gvsr3+/22YbwK+NPK90Mi8vci8jERefq4BojIa0TkHhG555FHHll5D8ad19+ZYtDa3JJWfdVNSJbaBYO3EBImnSOIQiQISnWTqkyI2ihafrA0G4UaJWYymuS2A7eBWNLckot24fcVVdXUjr4AUFoGhITpuFtrW33NX08HGDWsbiqYRIKqJv/TjklkWU7uq+l9z40H0f54I4ZUUqxoUl1EXHubRJE3SSusygj8BNpqBPxo8jq+URiL223ykwttEq2JiET1kJ2FkPB99kKiEMaBckKi7J+Zo7mlr+etqpsir19vR4ZtzW0kugcCvfnM1Qcfui8AiV9u9/ImPSM0vJAoAi6VF8SSnkJ7QVUIXeNzgBF2BxhaT885dZM49aGe2o+ytqywZ726qfBUaUcBeRF3ohyTkKgvJAqniUwYUDfpjnvu08q9C1kG80GTz5x3FcHOnWilyXwm00oF15JJhEGDKa/2C4cnZh1wy8Q7ePbkf3BZj4ewbX+Ha3/8Cu43eSkkxqmbAI48ZTexr8/QFxI+RcvxXvm+ufds4XNaCwonCYDz3/m20ft4A7PkKRKP9iAcxlteehW3XbgfQWiYBsfe9G/4s2sLW6LPdNx2zzYRSyPs32MJQmxmnbrJOBtkoIVObMqxr0xKmjt76KaxSYjIh0XksyP+7lzmNUY93QGLmIj8NE6w/q7f9CCw31p7NfBjwO+JFJVzhk5k7TustddZa6/btm3bqF1WhT6T8Ln5c0vqbRCBsUhngixbuMIpNPMmnSMIgyEmMWhULlROzbiIsIyrJyKzFqtcsXtdWS1UmYsOBpmEnXBql7yiQ02UWfDCF+3WeQ/d6h+vA3FMIrOlb76qJgdUmsyX7Ez9OYYT/Gnj6icXTKLlV0TFZKY6HbLTI5hEI+LdV/0/mEtcBDhFJt5C3eRfhnBISOgGhAcOYHY4QaHCCOVX1FHHTejNSLOjuQORfipzrUdPPIXBXekOjWYHnzWlLyT8OffF/UR4xbn0jCfDUVZO6BZLorvoPAAVoPMetrFjiEl0B/rYic2Ad1PbCnkopeApJtAc+qt2YN+VB7mi+X4Ohp91fUlyyCzGq/KMMmTaV/irConMCYlAN5jyNrJogZAIidVJmvr4QE6kKrZ2fG6qYZvEKL15NfWNFxK6MmlmaU6eW7Kk4gK7Tqiqm4J4tE4/KrbbtJ8LbAncedUefvmOV/LOb30nk9EkEz7g0FiL+PoZjchwWkYwibjZVzdpJxg6cVDaIgG06tHNvEoxW+g1thFY8s5ba2+z1l424u+9wEMisgvA/394xCnuB6p8bi9Qpv4UkVcAzwO+21rnDmKt7VprH/Of/w74EnBkdV1cHUqbxDCTEGgfOYRMzZAn+QBlB1BSFLuZJYgCt1IuCuEMCwlvvG54JhHrPkMQZclRrmaBzQaYBMC1z3HxBsZUbBJKgV/l2nbf6LiUTcJUhIQyCq2FPLVkWV5uK2CUIdWubkBalAoVb5MozqGFLOiVAWutyLB3usGhrU71o9ot8pOnFno36ZDT0XEaPpK9zyRaxc0FIBJnkwDIgh5xECMitG++maJBxb1ueJfbVmi468hd/Nqtv9bPGzTCAwYo82LFzRY7p/f3702zSNDo7vF21S9yX7AxE7o8TipWFDmEcpWSqgSdGywBKkvIzTQq7wuJwiYhI4SEttC0Qhr2mUTi7WMZdmCiibdt5+kzv1vq+tMkQzJL5PXbRkxZ20BXVqCtU/fxeOvr6CBkciyTqIzBMUJi2tvXCiFRGoSDEROZiFMpii6jt4e9ktJeNnIxtlYEoQZxae1HsUmAZrOo3Z0N2P2WQjNweacAOj6uI7AW6xlxHGhOKksqg/YkufS5YF125GIctCPDREWgKZUwn/n0PqVNYnMbrt8HvMJ/fgXw3hH7/C1wWEQOiUgIvNQfh4h8G/CTwPOtteWyTES2eYM3InIecBj48hrbuiIU3k3FoM0zS9LLMIEqV9pZtlDd1PIrfpPOEUbhgJQfFhJtLyTiKESL5sj2vrHNqbuUVzdl6CHD31Oefx6vfdszESVlShEVx3132E6feLmI6yFhVng35Qmm1RdO2rjkeFmWk6eFIbrCJETTM5mLkxjIAiuc9i6TjU5IaroI/biOv/zJW7nrOp9WpN1x6qYkGbDTNE2TQAVlmoPSJhEW6iZ3vljyPpOIMrb5KNf2M1xajLnP/kN5r5sTTkg0Q81UPMUz9j2jXDmqcUzCq5tazTY7pvpmMvH3SXlvrSnpF7kvzhU1A1qTEaY12bcfqIxMJQQ2AAlc3Yckc0zC17UobBLF5DARB6WQyE878TtnKO1HJZMQiKoTqwhM7i0jo5Ne7oRMEeGsDJnuYbHl5Dj1G/+eD93+fj5xwTtBh0x51rGQSVT9Z0cLialmyPnbWhzxBvG+umnMRGYiaEyVqzIzFN+QJfmG2CRECWFsBrychtFsFUIiR8XLYxLDCLWhkUFkLTYshITi76OUT4cpcYUFinfhtfPzpdqxExs6UYVJ6ITEp5DXdnDMbBTWKoLeBPyhiLwa+DpwF4CI7AZ+y1p7h7U2FZHXAx/E+Yb9trX2c/74Xwci4ENehfJx78l0M/ALIpLiHDh+wFr7OGcQw4Zrm1uyXu4CdYzQm89GDt5Qu1wJpZCoCIZhITG1owniJpbYxEzG/fQaosQFTYlG2RwVDA7SAWO5CCqOkUYDXUSSTlTUTdoQjmMSeQ892Y/NKGwSA0xCDzKJxzo5vUCTFOomn+DvMW258jUXsfO8CZKg7xIkwwKq0yGfnXW2g4rwawZN3vP897C37SfmC54FN/8EbLvIH+jjUSa2891X3smpz8H2ma38xm2/AUDrqU91uzWapbtxwSSqniKFrnncxFMEAbbaHXRFF10wCWnEYAzVW1qc6/rnHuTyZ+zht97bGhASqaSYPEAQdN4jn5sbcIG184W6ybWzE5vSjTn1RvZZTemunJZMYnA1Cjgh8Q03gdz7wAk0UroXa6VJVY9cZSWTiC+9nPyfcuLcokzIVFFTZTEmMcIm4c4vfORfPqP8vqi6qThnY6r8asLBaya9bENsEuDGQbiIkGi3nKB+bPd+pu562qquYZSilYMSC74YVWw0nw/d83t55R5XbZbFOPix248MPF+lKyVk8zOjblrT2b1K6Fkjtj8A3FH5/gHgAyP2G5m20Fr7HuA9a2nbmjGkbspzFydhArfSzrN0pJAwPgtnkMwSxSHxZZfR++pX3SmHJP6FT9nJlt1tmhMhu1q72N3a3b+8AsHlKxK7kEksaG6ziQpDtKfFemKQSSxQNxU69CzBtFsUuqK+TaJvuK6+oEYZUpWTao3YvuG6EEIzO9uICFlQyUk0ROcLF9Ls2LEFgvPQZMW/vTkDt/505UBvvLvj3/DdT302v/l7H6PVjtjqI4RVq8X+u+8m3LuH5KGHad10E42tWzBKaEb9e19MDOP03EW+rHa7jUT99hUxF6owjCuhORkye7xXjpfWZOSYRNwsV/0FkzDWCQmVJ+RzzvspE4XVmrxUN7k2taO+uinxkfnHFaXgqQqJxighIZ8H4NNfdmurtndHNsqQ6B65pGhvlNBBxMU9F1+sTFAarqNh18oBJrFM9YufwMZOZCYu7RHuEsPqptyrddc/7jdsmAEvp2FMtkOOASf2HKD99NUJCa2FZg65si5bLoNCfUDAV97xYq541sV9hwx3voqQsGfGBXZjRdA5jGJiGzRcOyahlLhJtBoJ6mHKILU54iigc/vtnHj/+0deQxtV+ub/znN+p3Shg0J94dVNNsOM8EsfaG8cI1GEKfTmk30mkWpTeieV+1eZRKeDOi7kufUusIK1fZXGgOFaNFZylNUoW6ibKIVQEU+RBf1UFsNCQnf69pLhdAiLQXwKCQkCTKiJmoaoNXh86ynOgyrYs4f97/wtAG6/ZAc3HNpS7lMyiTHqplxH5FaY7LQHDJbaCwkX0R0iSnP17fv5qz+6d4HaIoxbQ+qmFJ0HiHVCws7NomzuCilp089v5FeQRiu+92kH4c++Sfe4u5dHrR2pblrIJPZh+DQA//T145wPdPx90qLpqh6ZylBFDqgg4gePOZfZ+3TAZGOMTUJpZz+w2cg4iVEoF0ZjhUQ4ICSG1U1pLyvH5Xpj1wVT/dxJIzA5EXGMSuqMVcAooZn7+u8+IWLVG60q4AeYxJiJX1Xq6BZCYqNdYGshMQaFOqcfTOeZRKjKDK5ZagdUMQBBu4E+No+yOVEjov30b1nW9YZTkyutINdO3ZSngwNoBFSjgQQB8eWX8/Gdl3DdFS7luRUp8/pXUXo3ZT1UeyvqVF9IFL8lPtJ4WN2US4ayqoxTKLLAQkVIhBUhMaxuqhjVh5nE4p1UA8fc9KILmNrRWuwIAN72PdcOfC9Wj+MM1//YuoHHHn+cre24jJoHx9bc9aPSDnTVbfs5csNOmhOD/Yia7b53k2cSKjOuQFGekM/Po/KcXAQbBBWbRL9NL7/xAL/3Z98kncuwWB7P8wWG631bm1ywfSgL8MSe0ibxlW+c5HwCpjo+bkQFJKrnMv0WTCLsswIxEXGgiQO1UEi4mwZpNjLiehRkKSZx1XfBZN+vZVjd1J11K+eNUDc947suXPT36cmQr0E/nfcqoETY19UQpEjFcF1gwHBdVU2PseFUi0qZ/NywSTxxUbhzVgzXaZJjAo3Sjklkab5Ap3nRlW2Cj74LgFYzcnpskYE8PsuBUoLkqlQ3mWDxlZt4IXHDNReQvfM3uXiL4YuANQGX7J5csL+uRJPqThv1iEDiDNrFpF6oNKqrOC3aTTAEpbpJlJTG08IdMw8rZTmHhER48ED/S778+1I4ExQv08U37l5s97EIS8P1aCHx5c51/Fq6h19uhYPqplJIhC6quxCMEwsFnZmY9OoiS65yUpX0DflZQj4759VN2jGJItNs5YUvFip56oraHk3gr3ZdSoc+k3jDHRcz0xq6/uReV9+Zfj6/ae+aqkXzaPt+dBYw7ZmEMQGZFbRYlFcp/djtR7hq34gsOzqEdH7ZTGJJddPNg4WBxguJ9WcSS2H71hY9LI3J1a/UjRJe9GjMdepr/I3PJ1YVDANxEgNCYnR/TaWOrsEziVGeY+uIWkiMwbB3k7UFk9DeJmGdTWJoAtx5+T5mH/oEALu3uBXe4b/6S7LHHlvR9bVRSKpLdZMOFl9xT931IkS5XDY3nr+VfM4FpJk44k9ed9OC/dUAk+j4CTMrI66hyiT6fQxUQC45oYR9m4QIL7x6D1vbUenTnS9ik4gvvJBdb/q3PPiGNxLs2rX8myKDTGK1KAKpxq1OixX0lnY4oG6qCgk9NVV6OY1CsGMHb3yl5lu/DlZnAxUHVZ5g5+cQa8lFIDDkcz6WpjqZFobrJCcDTnZT/vvBp/LS06MFeInJfWgf1Bl7GdyoeDd9evefY/YaXqJcam+thHkCGvRQPjblNTefP7pjhV1imTaJxYLpRp7eKNdv3+7ubNLffoaxb3uLP7tA81M3rGCMDkFrIUMxS4zxTLiqbqrafWSE4XoYUtlsmF903/VCLSTGYDhOwrnA5sRtV9Amyyz5CBfYYE8/mLxIpWFmZjAzMyu6vkuL7b2b8hwdLr5ym77rroHvxYAbN6FqLwjivTtpXHUV6p98OnOfuwn6QmKASSjHJBqqWaqbULBjIuZF1/bdRatMYpSr6dQLXkD7llsGbCdLolA3LSEwl0LB/sZNPIXr59Z2hIRVIVHYJAL2vuVXB1K0D6MVtPjKLoH7LVbnAxUHVeHdlHubhAn6cRKVTKmFcM2SnEzgxFxKVAiO3kIBXmL6AOb8m+AxeMmVe/jqJx4uVSZaaVJfDa+wSYgIPcyAkBiLwsNppTaJZa52RQRjFFlmsbk9q0wiDjR/+n89Y03nMErI0JwmLt3Qx6qbgiqTGC1UTTXVu+2SsQmC6Z6skCHDtfWRnyZU6CK30Qivi2r0M2vQFWrvPVQE0y2lblrQfq0hCMYLCd/unT/0WprXXN3P5aQXZxKFTUJbw+uufL37XRZOVLaqbhoTrGSmpwcmxSX7pNaJSSyhbio9tVpOrVSgjLgOQ4LduxcV/M0y3xRYlfNYs4wfReUp+dw8Ks/IinTauX/5RzCJLHFlY3tZ3neL7RW1TEbcWx2gX/gW99HHupQFd5TBYknzvncTQI8ix9JSQsIziWXaJPrqpuWrbHSoaE25dmykTeJMQCshRTFr4zI1zqC6qSokqt5jo+eOvoOZxVBkgd3cCf6esBgdce3VTZ5JuEjQ8YN3LV4HRisETV7YJJZgEqOggmAgWG3gNzOoTiuFRNC3SYwSEoV3E7m7JzBaCCymblo1SiaxNm+OIF5c3VRUAJwZsknoqSnXjPZ4NVOBolqZKLDK8uDkl5j8jhM83Pqaq48+N+tqhYsa6foIg7EwRdrwwkutzyRGv8KFLa2YZAsmYby+wmLRqn+txAsJvRwmIXrQHXYRrFTdBM7DqchGMHvc6d0Xi2fYzDBK8ZH8Gv5b9rS+uqmysKx+Xo7huphStAGlRiwsNgDn5p0/A+gziWqcRI4JilTa+cgEfwBqcpL8+PE1GZSM0SirsaJWxSQAJIrGekUV7S4mj2KyUUPeTUoP5us3ypBKhvVCYhxLkNCSS46yamxk84qxXkxiCXXTTRds5bFTPeJA06swifYznsG+33w70QUjw3sG0CpSiYizSQBsPRLz5gf/Ay/+YI6dm0e8umlAXVCZuKvCtawtUagCk4XuyVUUfSvqZhQG4apgUJXyi91CSCw1+etwbLT1SJjCbXn578JlN++mMxPz4L3HOXXMCYkiGPBcgxL4/cyFkj2nSAKpFUYJaW7HezeNYQeFDNcmL5OQjo1mXyfUTGIMShfYqndTySQUeeoS4I0K8gl27lzz9ZXWaGuwKkDlGXo1QiIMx+rvi1V0X0h4oWjUAJMY7p8RgzGaPLNYaxeUeS2wpbGlZBPjBMlK0fduWtuEUbrAjhEStxzZxi+/+Ep3raq6KQpp33LLsq5RCAlRuORLwETgYmJsFJLPzXkmIQMrwYHJoXLbSiHhJ5VFDdf0x+04JgEMqJsSCehZvbRA18HYaOtRKCewFax2r7vjEEducO/QaR8jEjXPzfWsiPQzKFfeg0I4DAqJyrgew7y0L4WqdI74NDi1TeIsYaS6ydskykm0l418SaMLXS7CfHZuwW/LhdJCgDc+22ygnsRyUS2+M4w+kxhSN+k+k0h72QLvLa00oQnIc0uej7ZHAPz8jT/PtI/61mNUIiuGl0hLxYwshSKYbjg548hLVrN/ruBl3BJvQYli+irh5G5njygqmNnAuCRuBZNYhrqpiDY3ung2izMJpRWipC8kgsWZREJAwsKgywVYIZMo4yRWuNoVJZhAleqmc1VIQF9FaCrvQRwoQq0G7rdalrrJoOmiVdpnEnXE9dnBjoMTXHnbPnYdngKg5/XzplJkKE/tyKjdnT/7r4gvuYTm9det+vpKC7F1xkGx2arc3NRQ7qgqtu7rsP1ApyyF2o8wH7RJDE9CL7nwJXzp/uMc/4orfDOOJTSDJnEz5CTddWMSRbKkdVM3LUN4lS6wQbCgetli2Nbcxh8//485MHGAj/35H8E34PD0Ye44dAdB9NfYNC1tEhL0k/kNxElUmue9jQmM8w9dyiYBji325rzh1wuJQPUFUpVVpBKQWk20VB9VsEIhsUTupkWgQ0XXJzc8V9VN4BhEj0EmERlNVPFUgkFb27iJX0xAqOacu3tRg7xmEmcHJtR8y4sOl6qJZD4rtw8YckdE7ep2iy2vfOWKPHeGoZQQWDdBKZutyr4hjeagt1UFM7ta3PXG68t0EsVkM+wCO8yUnrb7aVzsE+5lvnzrOBSrv/WySch6xUkskeBv4JpeSKxmkjtv6jy00mjRhCokNjFvvvnNmCDCpkkZcT2gblqKSQypmxa7t9WxWbrAyhgmIQE9zFhmWDnp8j2boFzcrGb8FukwlJIFQXbnEvpMoqpuUgtybg3GSYxLyxEQyixKkr66qY6TOLsoV9XzfSZRlPWEjfPfVkowuXdLzLNVTVI7f+qNg+qSxa43YJPoG66LCbWKghlk6XgmARUhsZ7eTUqtWQdbpgpfjropXL2QKKBFE1YyqEoQYHvOXpMtyiSkehLXdj/xJ6UL7PjxZ4yii4+iL/XiFZvEgHdTSLocddP0QYg6i+9TQSn0VuEOXgi2qGVWxOI2G0x576vqJk2SDWYbGPRuGmOTMAG7w89ztHmwr26qI67PLoqXqzffNwDaSlnKdfPcGYJoQWVFZaxsVflZGlddtex9i35UvZvmTydMbFmoWijUNFmyhJBoFPro9RISsmb3V3DP9GkvPJ99Fy8d4FhUuFuTkFBDQsIYrK9Et7hNotoQ9yWs2ItgeUyimqCuKhiqrCKVgMRqlpTnz/vVJXYYQqluWvlzK9jDuaxqAkYarhuBJsmG1E3LYBKiQ26dfCv/e8f3QqFuqnM3nV1IKSR86dJQk1ce7oYxCS1IJn6FmS2x93pcr1A39W0SWIjbC1U7ZW6npYSEf7nXi0mIqDWrmgpc860Hlt6JtambCihRA0KCoCokZHACHcMkxNcpCUp10+KGa4DmRMSJR+fZ7e1qMMgkquqmo2qaNpPsX9ImsbLxXqhCVnP/CtXauWy0htHqplZkyOxiTGJ0n3VxH5O5iuF6E2eBFZEZ4A+Ag8BXgRdba4+O2O/bgLcAGleM6E1++88B3w884nf9KV97AhF5I/Bq3Az5Q9baD66lratFMcElXW8ADBWqV0lTsYHqJpu5a9szIiSqEdeVFU9n4QAs+pwl+aIrzx3nTbDj0MT6sS2t101ILBelum4NlH53azePzfVzd4kJyHsVJlGs9JUaKiZVaYcqhMQgk1hs/D33dVeQpTmtyb7KcZwL7H9qvpIHZo/xN6vo32LoFx1ajbrJM4lzNJCuQKFmqqqbfvLbLlrIJLR2i4QsG3u/ymDHdL7iAru5mcQbgI9Ya98kIm/w33+yuoMvQ/pW4HZcveu/FZH3WWs/73f5FWvtvx865hJcmdNLgd3Ah0XkiK3qec4QXIW4vk0iCBW9quF6g9IFVFffVja+21o7BiFKBiaeRmcEkzDLYxLnX72d86/evm5tDHbvJty3b+kd1xF9m8TqV2s/fM0Pk9OfECQIykp0OVJxEx0yZFYFhhFIICyFxNJMIm4tbPM4JpGYFsdkZZmKl4ViAlsNkwifuEzikt0TI/eVIMBm2fg4CT8OJZ2vMInN7d10J3C3/3w38IIR+9wA3Gut/bK1tge82x+31Hnfba3tWmu/Atzrz3NWoERKdZMO9MAkuhEVs2DQtfFMMYmyEFHl2o32CCah+6vZdXNvXQa2vu61HPi93z1j1wPK2sZrtUlUXU/H2iSGrlG9t8UzCf2kWzgNrNSgW2UPg0ZstbTRehUohOuT2SZhRtgkxqFMzDlmvBVMQmV9JrHRNom1znA7rLUPAvj/o5aNe4D7Kt/v99sKvF5EPiMivy0i08s85oxCtFQM14PqmI1SN1WNvfkZYBJK911fB9VN45nEUt5N6w0RWZNb8aquaYxTc63jak2MIa8ICeUjbYf7NuAB6+95VHEFXc0KexyTMErQG+BBtDZ1kzsmPMeZhFIu6no5Ar0UEuOYhF9QVIXERtsklnzjROTDIvLZEX9LsYHyFCO2Fbz2bcD5wFXAg8AvL+OY4fa9RkTuEZF7HnnkkVG7rBmipKJu0gNBWBtpk+gjH7vfekEbKQ2FVRXaSJtEJer3HPZMXDYkitZXSARBySSyquF6mEnIwsVIFOhybIwqdrQUBthDhVVoJevnqjxwwdUH0xX2l3Nd3WSULItFQCU1x7iIaz9WTNYt372zbpOw1t427jcReUhEdllrHxSRXcDDI3a7H6gqkvcCD/hzP1Q51/8LvH+pY0a07x3AOwCuu+66DVCqugm71+1HrlZX2svxtV/tNQvMNKcX2XN9cMWz9nHoqm3u2lWbxCjvpopNYlQcxRMNKgzXZLgehgT9mtb7traJGhGzjF49ihJsbvtMwmjHMnM7kuUthXFxEkbJxqibVpG7qYD2TCI+x9VNegVCQgWFumkck3C/m7yL6HMjd9P7gFf4z68A3jtin78FDovIIREJcQbp9wF4wVLghcBnK+d9qYhEInIIOAx8Yo1tXTWUEnIfQBf4ynQFNtIFtrzGGVDpbNnd5uDlW931lvJuWmacxBMFjkms40RlDHnPJa77F888jC48tkak2ChziPlJIzJqTUxiXMS1VrJ0tPUqUKblWEVUcN8m8QRgEsvMX1YyiTFq1cCPw9DOY4vntckjrt8E/KGIvBr4OnAXgIjsxrm63mGtTUXk9cAHcS6wv22t/Zw//pdE5CqcKumrwL8AsNZ+TkT+EPg8kAKvOxueTQWqOXT0sE1ivZLXDV+zylY2KGBv7LWrQT8jbRJe3ZRk53Qk7HIhUbQuQXzl+SrqJlGaxZLguftrMYFnEhUmO0qAL4VxwXSOSaz4dMu44MpThRcIniA2iZUwCQkWN1wb/3tge+RFVuTNHHFtrX0MeNaI7Q8Ad1S+fwD4wIj9Xr7IuX8R+MW1tG+9UKY0CJTPklrN3bTx6ibTXEH+/nWAiLhUDiIE0ULaqwdcYM9o084KVBSus+E6KCvRidGlABpllO8zCe/dpF1pT1ilTUJGG671hhmu1xBM55nEua5uMkoNuL8uhqUM14WQiOiRF/VV6ojrs49iVd/xKSqUOrPqph0/8kMbco3FoLUa6WcPDERkb4ixc5MhPHgQs23bup1vuMjQOBdY6LO6Mvo40JzwGYnXapMYCKzbIMN1qVtfhUqkcH1dDWPaTFBqMJBuMZTBomNThbvfG3Tp6fHjZj1RC4lloHh5SiFhqqqgjfJu6p833Ll+AWnLvr6RsS9ntc9PBpvE3v/4H9f1fDKQ9VWV6oKRhuuCSRT6+cqiZK3eTdUxZjYoTqJf43rlU83512yjOXkV7ekzy6TXG6tiEmMM14EXElOc5gGz0+9bC4mzDimFhK+9cAbiJNRZtEm4a6qxK9Wquu3JYJNYbwzYN6pMYpThukjsF/QN1wXWariufr54Vwc72st8TZA1pAo3gWbfRUsnYdzsWJFNYgl1U3E/lVhkb5upu55DeOjQ+jR0DGohsQxkvp5wkRFVD3g3bcwkOSra9kyi0Q5K5jSMQSZxplr0xMHAhKlVf7U91nBdiRmorDDX7AJbERKvv/Xwis+1HPTVTU98V+lxcHESy1Q3LaJ6BFzRp+LjzDS7fuhfr7V5S6IWEsvAqaPOE6WYNM9IMN1ZZhLPe/2VZQW3YVT7XDOJVWCoyFBpuB4ZJ+H+h0Ueo0ohoeYahYQ6ExK+jLh+8k41N12wlYdPdpe171JMgqpNqbXx8VNQC4kVobRJnIlgurMsJDoz4/XA1fY8GWwS641BdVMld9OoicEL4ch7mcUVJjGqKuJSGJcFdqPQ9246t43Pa8GrvmX56qAiTmKskKiwzbizZU3tWi5qZcEKMFHYJKousBtmuN74a6wWAwkON1fTzglUJ0zRup8Eb8TEUAyDS/ZO8tN3XMx1B9e2eqzGSagz8PD6Na6fvOqmlaDv3TSOSfTHTnPyzAiJmkmsAIW3T6GTL1JrbwTONpNYDFUhWTOJlWPQBbaaBXZ8qdg4Mnz/zeet+drjXGA3DLW6aUVQK1A36cbUGWhRLSRWhEL/rpQgsnFpwmHYcL25JuIqy6mFxMpRNVy7QjM+claNUje5f1XB/KI3XLfqmIZxwXQbhVI41EJiWVhU9QigK2q7WkhsHhy+fkdZCayAGoq8Xm9sZiZRRGTnqa0N16vAApvEIum0C2FQVfHtODi6YM1yMC4tx0YhuuACwgvOJ9y/f8Ov9URAeL67X2NT4lcFezx1RtpUC4ll4NmvvnTBNmVkQ20F5UpRNudqXWtFnmZPilTh644x3k0jo2xloZBYC5QolChymw8IjI1CuH8/57///UvvWAOAqRe+gKkXvmD8DiLOLpEnZ0xI1GbHVUJp2TD3V3f+it1jE87EhfrjyZCWY70x4OlTsUkslrtpPcdawSDOiAtsjfVHYZc4Q+qmepSsElqrDXN/hf7kezYC6ZaDgkVtRpaz2VFVN0m16t2o3E0Fk1iFu+s4FMbrM6FuqrEBKOwSNZPY3FBmY5lEkVRQbzJ7RIFCQNZCYuUYl+BvJJNQ6z8OCuN1zSTOUdRM4tyAM1xvpLpJBv5vNvSZxFluyDmIQe+mJVxgN0DdVDCJqjtsjXMIxXOLJ8/M5c7IVZ6A0Fo21rtJbW6df+H+uxHVzJ7oGGYSlMF0o9VNSq1vPE5hsK6ZxDkKHUDQGnSH3UCsaZSIyIyIfEhEvuj/jwwHFZFvE5EviMi9IvKGyvY/EJFP+b+visin/PaDIjJX+e3ta2nnRuDMMYnN+SLrWt20agzaJFQlFcModROodbRHQG2TOOeh9BlTNcHaXWDfAHzEWvsmP/m/AfjJ6g4iooG3ArcD9wN/KyLvs9Z+3lr7ksp+vwwcrxz6JWvtVWts34bBhAodbNxLJmpzq5tUbbhePYZtEsX3MUxivRlrIRxqIXGOQgUQds7Y5dYqJO4EnuE/3w38BUNCArgBuNda+2UAEXm3P+7zxQ7iXDheDNy6xvacMXzLXYfX1eNkGJveJlEwic3ZvE2NwdxNavEssLL+ubsCn/+nVjedo1DmjNkjYO02iR3W2gcB/P9RJdT2APdVvt/vt1XxdOAha+0XK9sOicjfi8jHROTp4xogIq8RkXtE5J5HHnlkdb1YBXaeN8m2fRsnzTe7C2zNJFaPgYhrbZYsOrTeas2SSZyBYLoaG4DWVpjce8YutySTEJEPAztH/PTTy7zGqFlkuATWy4Dfr3x/ENhvrX1MRK4F/kRELrXWnlhwImvfAbwD4Lrrrlv/0lpnCQWD2Ejj+FpQ2yRWjwXeTVqDyFjD9Xoz1sImUTOJcxR33b2qmuGrxZJXstbeNu43EXlIRHZZax8UkV3AwyN2ux/YV/m+F3igcg4DfAdwbeWaXaDrP/+diHwJOALcs1R7nyioRlxvRpTtq/VNK8YC7yYcuxiVu0nU+i8UCgZR2yTOUbS3ndHLrXUp8T7gFf7zK4D3jtjnb4HDInJIRELgpf64ArcB/2Stvb/YICLbvMEbETkPOAx8eY1tPaew2dVNfSZxlhtyDkLMIJMAaFxzDdGRCxfuK+uvbjLKIEjNJGosC2vlLG8C/lBEXg18HbgLQER2A79lrb3DWpuKyOuBDwIa+G1r7ecq53gpg6omgJuBXxCRFMiAH7DWPr7Gtp5TqL2bnrgYtEm41fyBd/2nkfuaQK27c4ARU7OIGsvGmoSEtfYx4Fkjtj8A3FH5/gHgA2PO8coR294DvGctbTvXcc54N9VCYuWoejctUR3uxhddsNCCt9bLK1MbrWssG3Vc/ibFZg+mKyKua5PEylE1XI8tLuOxZXd73a+vRdeqphrLRj1SNinUJlc31VlgV4+BiOuzUCRcK12rm2osG7WQ2KSQTa5uqutJrB4D3k1LMImNgFGmZhI1lo16pGxSnDNMotY3rRgD3k1ngUkYMXUG2BrLRi0kNilEXObPzWuTqF1gV42aSdQ4h1CPlE0MpWTzM4la3bRiiAgsUmhoo6FVbbiusXzUnHMTQ7Sse3K39UJtk1gbxBhsnp+Va+9t7+WB9gNL71ijBrWQ2NQ4ePkWdp4/cbabMRK1TWJtEGMgTc/KtV971Wv5QfuDZ+XaNc491EJiE+Nbv++ys92EsajTcqwNEgTYJDkr11aiRqfdrFFjBOpXvMaq0A+mq2eb1UCMOSv2iBo1Vop6lNZYFbSu03KsBWLMWfFsqlFjpaiFRI1VoWASteF6dZAgqJlEjXMC9SitsSr0XWDPckPOVQQ1k6hxbqB+xWusCqrOArsmiAlGliutUWOzoR6lNVaF2gV2bXCG65pJ1Nj8WJOQEJEZEfmQiHzR/58es99vi8jDIvLZ5R4vIm8UkXtF5Asi8q1raWeN9UcdTLc2SBC42tY1amxyrJVJvAH4iLX2MPAR/30U3gV823KPF5FLcBXrLvXH/UZRzrTG5kBZUrOWEatC7d1U41zBWoXEncDd/vPdwAtG7WSt/Z/AqPKj446/E3i3tbZrrf0KcC9wwxrbWmMdURZFqpnEqiBBHSdR49zAWkfpDmvtgwD+//Z1On4PcF9lv/v9tgUQkdeIyD0ics8jjzyywsvXWC2mtjfZe9E02/Z3znZTzk0EQc0kapwTWDIth4h8GNg54qefXv/m9C87YtvISr/W2ncA7wC47rrr1rkacI1xCBuGO3/k6rPdjHMWYgKk9m6qcQ5gSSFhrb1t3G8i8pCI7LLWPigiu4CHV3j9ccffD+yr7LcXqNNW1njCYPq7XkZ29NjZbkaNGktirUuZ9wGv8J9fAbx3nY5/H/BSEYlE5BBwGPjEGttao8amQfumm5h83nPPdjNq1FgSaxUSbwJuF5EvArf774jIbhH5QLGTiPw+8NfAhSJyv4i8erHjrbWfA/4Q+DzwP4DXWWuzNba1Ro0aNWqsEGLtE0eNf91119l77rnnbDejRo0aNc4piMjfWWuvG/VbbTmrUaNGjRpjUQuJGjVq1KgxFrWQqFGjRo0aY1ELiRo1atSoMRa1kKhRo0aNGmNRC4kaNWrUqDEWTygXWBF5BPjaGk6xFXh0nZpzLqHu95MLdb+fXFhOvw9Ya7eN+uEJJSTWChG5Z5yv8BMZdb+fXKj7/eTCWvtdq5tq1KhRo8ZY1EKiRo0aNWqMRS0kBvGOs92As4S6308u1P1+cmFN/a5tEjVq1KhRYyxqJlGjRo0aNcaiFhI1atSoUWMsNq2QEJF9IvJREflHEfmciPyw3z4jIh8SkS/6/9N+++0i8nci8g/+/62Vc13rt98rIr8mIqPKo47dT0R+RUQ+5f/+WUSOjTn+x0Tk8yLyGRH5iIgcqPz2ZhH5rP97ySbr9y+KyH0icmpoeyQif+CP/xsROTjm+JtF5JMikorIi4Z+yyr37n3nSL/HPseV7CciEyLyDRH59XH93oC+j+zTiGuOG+s/4Ld/SkT+UkQuGXP8yGcuIleJyF/7fnzmDI71tfb7lSLySGWsft+Y40c+cxF5ZuXYT4nIvIi8YLG2nDOw1m7KP2AXcI3/3AH+GbgE+CXgDX77G4A3+89XA7v958uAb1TO9Qngabja2X8KPGfMNZfcD/g/gd8ec/wzgab//IPAH/jPzwU+hCsX2wLuASY2Ub+f6q97amj7a4G3+88vLfoz4viDwBXAfwZeNPTbqVHHbPJ+j3yOy33eld/fAvwe8OtnsO8j+7TcsV4dl8Dzgf+xkmcOHAEO+8+7gQeBqXOg369c6jktd2wAM8DjxX7n+t9Zb8CyG+pKm94OfAHYVRlkXxixrwCPAZHf558qv70M+M0Rxyx3v/8N3L6M9l4N/JX//OPAz1R+eyfw4s3Q76HjhyfLDwJP858NLmpTFjn+XaxSSGymfo97jst93v77tcC7lzv5rEffV9Cn5Y71lwF/ukRbFzzzod8/jRcam7nfq3xOI8cG8Brgd1cz7jfj36ZVN1Xh1RxXA38D7LDWPgjg/28fcch3An9vre0Ce4D7K7/d77cNY8n9PLU8BPz5Mpr9atxKBdyL8hwRaYrIVtxqZN9SJzhD/V4Me4D7/DVT4DiwZYXniEXkHhH5+HLp9ybodxXV57is/UREAb+MWxysCGvs+3Kx6D0SkdeJyJdwK/ofWlEHKhCRG4AQ+NIy9j3IWe438J1ejfRHIrLk+8n4sfFS4PdX0K5NDXO2G7AURKQNvAf4EWvtiTHq5er+lwJvBp5dbBqx2yi/3+Xs91Lgj+wS9bZF5HuA64BbAKy1fyYi1+NYyCO4et/pEuc4U/1e9LTrcI791toHROQ84M9F5B+stWMnjU3S7+LcA89xBfu9FviAtfa+pdo/dJ619n3ZlxqxrbxH1tq3Am8Vke8CfgZ4xQrPj4jsAn4HeIW1Nl9i383Q7/8G/L61tisiPwDcDdw6Yv+iDSPHhu/35TgW/sTA2aYyS9C5AHezf6yybSwVBfbi9Jo3VbaNpJiABj7l/35h3H5D7fl74MbK918szlHZdhvwj8D2Rfr1e8Adm6HfQ9ddlrppVL/9Pu9icdXDUr9vin6Pe47Lfd7A7wJfB77q79kJ4E0bPdbH9Wm47+Pu0YhzKOD4uL6Pe6bABPBJ4K4z8Y5vQL/1Yv0e9cwrv/0w8I6l+n0u/Z31BiwyeARnFPvVoe3/jkGj1i/5z1M4tc53jjjX3+IMW4WxauQEvdh+wIX+pV9MJ381jlofHtqugS3+8xXAZwGzWfpd2X9YSLyOQcP1Hy5x/MCEAUzjdca4TJRfBC45B/o98jku93kP7fNKljZcr1vfx/Vpufeo2hfg24F7VvjMQ+AjOFZwxt7xdej3rso+LwQ+vppnDnwceOZSfT+X/s56AxZ5mN+Co4Kfob8auAOnE/+In3A+Asz4/X8GOF3Z91N4SY+jhZ/1D/fXGTPRL7Yf8HMsvRr8MPBQ5frv89tj4PP+7+PAVZus37+E08/m/v/PVdr9X4F7cV4h5405/np/3GmcMfFzfvuNwD/4F/sfgFefI/0e+RyX+7yH9nklSwuJ9ez7yD4td6zjPLI+58/5UeDSFT7z7wGSobaNHO+brN//1vf7077fF630meM8vr4BqDM5V270X52Wo0aNGjVqjMU54d1Uo0aNGjXODmohUaNGjRo1xqIWEjVq1KhRYyxqIVGjRo0aNcaiFhI1atSoUWMsaiFRo8ZZwFLZSmvU2CyohUSNGjVq1BiLWkjUqLFOEJHvEZFP+HoCvykiWkRe5usXfFZE3jy0/y/7mgwfEZFtZ6vdNWoshlpI1KixDhCRi4GX4HIKXQVkwHfjEtHdClwFXF/JhNsCPmmtvQb4GPCvznCTa9RYFjZ9FtgaNc4RPAtXQ+JvfRbTBq64zV9Yax8BEJHfBW4G/gSXPuIP/LH/Bfj/znB7a9RYFmomUaPG+kCAu621V/m/C4GfX8HxdX6cGpsStZCoUWN98BHgRSKyHVydZlxq+VtEZKuIaFxq6o/5/RVQ1Ib+LuAvz3B7a9RYFmp1U40a6wBr7edF5GeAP/OV6RJcqvU34rKKCq4Q0Xv9IaeBS0Xk73AV/15yFppdo8aSqLPA1qhRo0aNsajVTTVq1KhRYyxqIVGjRo0aNcaiFhI1atSoUWMsaiFRo0aNGjXGohYSNWrUqFFjLGohUaNGjRo1xqIWEjVq1KhRYyz+fxp4SQSAgP6RAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "r1.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c771c705",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>symbol</th>\n",
       "      <th>SZSE.000001</th>\n",
       "      <th>SZSE.000002</th>\n",
       "      <th>SZSE.000063</th>\n",
       "      <th>SZSE.000413</th>\n",
       "      <th>SZSE.002007</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>eob</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-29</th>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0302</td>\n",
       "      <td>0.0143</td>\n",
       "      <td>0.0661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-30</th>\n",
       "      <td>-0.0126</td>\n",
       "      <td>-0.0085</td>\n",
       "      <td>-0.0159</td>\n",
       "      <td>-0.0176</td>\n",
       "      <td>0.0192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>-0.0022</td>\n",
       "      <td>-0.0015</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-03</th>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0214</td>\n",
       "      <td>0.1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-26</th>\n",
       "      <td>-0.0647</td>\n",
       "      <td>-0.0757</td>\n",
       "      <td>-0.0060</td>\n",
       "      <td>-0.0095</td>\n",
       "      <td>-0.0435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-27</th>\n",
       "      <td>-0.0553</td>\n",
       "      <td>-0.0562</td>\n",
       "      <td>0.0172</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-0.0156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-28</th>\n",
       "      <td>-0.0006</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0141</td>\n",
       "      <td>-0.0577</td>\n",
       "      <td>0.0281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-29</th>\n",
       "      <td>0.0118</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0070</td>\n",
       "      <td>0.0153</td>\n",
       "      <td>-0.0030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-07-30</th>\n",
       "      <td>-0.0150</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.0333</td>\n",
       "      <td>0.0352</td>\n",
       "      <td>0.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>247 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "symbol      SZSE.000001  SZSE.000002  SZSE.000063  SZSE.000413  SZSE.002007\n",
       "eob                                                                        \n",
       "2020-07-28          NaN          NaN          NaN          NaN          NaN\n",
       "2020-07-29       0.0150       0.0089       0.0302       0.0143       0.0661\n",
       "2020-07-30      -0.0126      -0.0085      -0.0159      -0.0176       0.0192\n",
       "2020-07-31      -0.0022      -0.0015       0.0067       0.0036       0.0648\n",
       "2020-08-03       0.0187       0.0164       0.0084       0.0214       0.1000\n",
       "...                 ...          ...          ...          ...          ...\n",
       "2021-07-26      -0.0647      -0.0757      -0.0060      -0.0095      -0.0435\n",
       "2021-07-27      -0.0553      -0.0562       0.0172       0.0000      -0.0156\n",
       "2021-07-28      -0.0006       0.0164       0.0141      -0.0577       0.0281\n",
       "2021-07-29       0.0118       0.0054       0.0070       0.0153      -0.0030\n",
       "2021-07-30      -0.0150       0.0029       0.0333       0.0352       0.0000\n",
       "\n",
       "[247 rows x 5 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1=(stock_close-stock_close.shift(1))/stock_close.shift(1)\n",
    "r1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "2d43b633",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='eob'>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "r1.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f0d495a",
   "metadata": {},
   "source": [
    "## 多期与单期的关系\n",
    "\n",
    "### 年化收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "f6855bed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.016"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.008+0.008"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d1c8960b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.016064000000000078"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1*(1+0.008)*(1+0.008)-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "fe227ff3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.008032000000000039"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.016064000000000078/2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ccdd55e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.008000000000000007"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(0.016064000000000078+1)**0.5-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3a49b8b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.30822222222222223"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(0.0076/9)*365"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "601d6a02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.48406866689184724"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(0.0076+1)**(365/7.0)-1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fb442fa",
   "metadata": {},
   "source": [
    "### classwork2\n",
    "\n",
    "* 选择输出000413 2021-01-08 这天的二期收益，比较其2021-01-07与2021-01-08单期收益之和的关系\n",
    "\n",
    "* 请通过单期收益率计算严格的二期收益率\n",
    "\n",
    "* 计算 '000413的2021-01-11这天的七日收益率，并基于此求七日年化收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "1128cea2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.09842519832859187"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((stock_close[\"SZSE.000413\"][\"2021-01-11\"]-stock_close[\"SZSE.000413\"][\"2021-01-05\"]))/stock_close[\"SZSE.000413\"][\"2021-01-05\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "34475376",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-3.515185654592567"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-0.09842519832859187/7)*250"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "a85daa7f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.9752873010373428"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1-0.09842519832859187)**(250/7.)-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d0b43135",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.04799995422363281"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r2[\"SZSE.000413\"][\"2021-01-08\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "7fcc6977",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.0479999542236329"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1+r1[\"SZSE.000413\"][\"2021-01-07\"])*(1+r1[\"SZSE.000413\"][\"2021-01-08\"])-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "decf9d78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-10.999988555908203"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "-0.04799995422363281*250"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "c9e8b7bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "123115.40325744804"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1+0.04799995422363281)**250-1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dab20ce7",
   "metadata": {},
   "source": [
    "# 资产风险的测度\n",
    "\n",
    "* 此部分可以参考《量化投资以python为工具》电子书的284页（同时也是书上的266页）\n",
    "\n",
    "\n",
    "### 风险——方差\n",
    "\n",
    "### 最大回撤\n",
    "\n",
    "就是从任一高点到其后续最低点的下跌幅度的最大值\n",
    "\n",
    "https://zhuanlan.zhihu.com/p/91249594\n",
    "\n",
    "### 夏普率\n",
    "\n",
    "夏普率(sharpe ratio): 衡量策略相对于无风险组合的表现，是策略所获得风险溢价的度量——即如果策略额外承担一单位的风险，可以获得多少单位的收益作为补偿\n",
    "\n",
    "假设国债利率是3%（既无风险回报率3%），投资组合预期回报利率是13%、标准偏差是5%，超出无风险投资回报为=13%-3%=10%，夏普比率=10%/5%=2，意味着投资风险每增长1单位，可产生超额收益2单位\n",
    "\n",
    "https://wiki.mbalib.com/wiki/%E5%A4%8F%E6%99%AE%E6%8C%87%E6%95%B0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "08e5e9d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "a1=pd.Series([1,4,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "76ef134f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    4\n",
       "2    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "4fd3333d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.666666666666667"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "((a1-a1.mean())**2).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "12407aeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.666666666666667"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a1.var()*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a227f3d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.666666666666667"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a1.var()*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "59b91a90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0006466586875528915"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1.loc[\"2020-07-29\":][\"SZSE.000413\"].var()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e41dc33b",
   "metadata": {},
   "source": [
    "## classwork2\n",
    "\n",
    "* 计算SZSE.000063的全部时间的风险\n",
    "\n",
    "* 计算SZSE.000063的夏普率，假设无风险回报率3%\n",
    "\n",
    "* 计算SZSE.000063的最大回撤"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "51e17143",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.02357763122555496"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1[\"SZSE.000063\"].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7340ea3f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "56e74e08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0283004702328493"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(((r1[\"SZSE.000063\"][\"2021-07-30\"]-r1[\"SZSE.000063\"][\"2020-07-29\"])/r1[\"SZSE.000063\"][\"2020-07-29\"])-0.03)/r1[\"SZSE.000063\"].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "cd5d9175",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.10009822981183504"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1[\"SZSE.000063\"].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "32501de5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1880103149991616"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hc=[]\n",
    "for i in r1.index:\n",
    "    hc.append(r1[\"SZSE.000063\"][:i].max()-r1[\"SZSE.000063\"][i])\n",
    "    \n",
    "max(hc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "ba6b8b30",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "eob\n",
       "2020-07-29    0.0302\n",
       "2020-07-30   -0.0159\n",
       "2020-07-31    0.0067\n",
       "2020-08-03    0.0084\n",
       "2020-08-04   -0.0157\n",
       "               ...  \n",
       "2021-07-26   -0.0060\n",
       "2021-07-27    0.0172\n",
       "2021-07-28    0.0141\n",
       "2021-07-29    0.0070\n",
       "2021-07-30    0.0333\n",
       "Name: SZSE.000063, Length: 246, dtype: float64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1[\"SZSE.000063\"][:\"2021-07-30\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "aeb0b8ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06680929208029299"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r1[\"SZSE.000063\"][\"2021-07-30\"].max()-r1[\"SZSE.000063\"][\"2021-07-30\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "06012fcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "eob\n",
       "2020-07-29    0.0302\n",
       "2020-07-30   -0.0159\n",
       "2020-07-31    0.0067\n",
       "2020-08-03    0.0084\n",
       "2020-08-04   -0.0157\n",
       "               ...  \n",
       "2021-07-26   -0.0060\n",
       "2021-07-27    0.0172\n",
       "2021-07-28    0.0141\n",
       "2021-07-29    0.0070\n",
       "2021-07-30    0.0333\n",
       "Name: SZSE.000063, Length: 246, dtype: float64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in r1[\"SZSE.000063\"]:\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7572bed",
   "metadata": {},
   "source": [
    "# 第一个策略的编写与运行\n",
    "\n",
    "https://www.myquant.cn/docs/python/python_basic\n",
    "\n",
    "* 定时任务\n",
    "\n",
    "* 初始化函数 ini\n",
    "\n",
    "* 定时运行函数 elgo\n",
    "\n",
    "不同的函数运行次数是不同的！\n",
    "\n",
    "init 函数最开始运行一次，其他函数运行次数由相关函数决定"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "625bf31d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# coding=utf-8\n",
    "from __future__ import print_function, absolute_import\n",
    "from gm.api import *\n",
    "def init(context):\n",
    "    # 每天14:50 定时执行algo任务,\n",
    "    # algo执行定时任务函数，只能传context参数\n",
    "    # date_rule执行频率，目前暂时支持1d、1w、1m，其中1w、1m仅用于回测，实时模式1d以上的频率，需要在algo判断日期\n",
    "    # time_rule执行时间， 注意多个定时任务设置同一个时间点，前面的定时任务会被后面的覆盖\n",
    "    schedule(schedule_func=algo, date_rule='1d', time_rule='14:50:00')\n",
    "def algo(context):\n",
    "    # 以市价购买200股浦发银行股票， price在市价类型不生效\n",
    "    order_volume(symbol='SHSE.600000', volume=200, side=OrderSide_Buy,\n",
    "                 order_type=OrderType_Market, position_effect=PositionEffect_Open, price=0)\n",
    "# 查看最终的回测结果\n",
    "def on_backtest_finished(context, indicator):\n",
    "    print(indicator)\n",
    "if __name__ == '__main__':\n",
    "    '''\n",
    "        strategy_id策略ID, 由系统生成\n",
    "        filename文件名, 请与本文件名保持一致\n",
    "        mode运行模式, 实时模式:MODE_LIVE回测模式:MODE_BACKTEST\n",
    "        token绑定计算机的ID, 可在系统设置-密钥管理中生成\n",
    "        backtest_start_time回测开始时间\n",
    "        backtest_end_time回测结束时间\n",
    "        backtest_adjust股票复权方式, 不复权:ADJUST_NONE前复权:ADJUST_PREV后复权:ADJUST_POST\n",
    "        backtest_initial_cash回测初始资金\n",
    "        backtest_commission_ratio回测佣金比例\n",
    "        backtest_slippage_ratio回测滑点比例\n",
    "    '''\n",
    "    run(strategy_id='strategy_id',\n",
    "        filename='main.py',\n",
    "        mode=MODE_BACKTEST,\n",
    "        token='token_id',\n",
    "        backtest_start_time='2020-11-01 08:00:00',\n",
    "        backtest_end_time='2020-11-10 16:00:00',\n",
    "        backtest_adjust=ADJUST_PREV,\n",
    "        backtest_initial_cash=10000000,\n",
    "        backtest_commission_ratio=0.0001,\n",
    "        backtest_slippage_ratio=0.0001)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd33d4f1",
   "metadata": {},
   "source": [
    "## 掘金平台下的股票代码\n",
    "\n",
    "\n",
    "上交所 SHSE\n",
    "\n",
    "深交所 SZSE\n",
    "\n",
    "## 不同的交易函数\n",
    "\n",
    "\n",
    "order_volume - 按指定量委托\n",
    "order_value - 按指定价值委托\n",
    "order_percent - 按总资产指定比例委托\n",
    "order_target_volume - 调仓到目标持仓量\n",
    "order_target_value - 调仓到目标持仓额\n",
    "order_target_percent - 调仓到目标持仓比例（总资产的比例）\n",
    "order_batch - 批量委托接口\n",
    "order_cancel - 撤销委托\n",
    "order_cancel_all - 撤销所有委托\n",
    "order_close_all - 平当前所有可平持仓\n",
    "\n",
    "\n",
    "## classwork1\n",
    "\n",
    "* 请找到贵州茅台股票的代码，并在2012年第一个交易日开始每天买入100股，直至钱花光，看20200101的收益\n",
    "\n",
    "* 并在2012年第一个交易日开始每天买入100000金额的贵州茅台股票，看20200101的收益\n",
    "\n",
    "* 请找到贵州茅台股票的代码，并在2012年第一个交易日开始保持仓位500股贵州茅台，直至钱花光，看20200101的收益\n",
    "\n",
    "* 一开始就买入100%资金的股票"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc6f369a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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